Office

Top Read Articles

    Published in last 1 year |  In last 2 years |  In last 3 years |  All
    Please wait a minute...
    For Selected: Toggle Thumbnails
    Design and analysis of an improved OMU-NRDCSK communication system
    ZHANG Gang,LIU Jinhui,ZHANG Peng
    Journal of Xidian University    2020, 47 (4): 1-9.   DOI: 10.19665/j.issn1001-2400.2020.04.001
    Abstract648)   HTML247)    PDF(pc) (1356KB)(550)       Save

    Aiming at the shortcomings of a low transmission rate in traditional Differential Chaos Shift Keying (DCSK) and a high bite error rate when transmitting multi-user information, an improved orthogonal multi-user noise reduction differential chaotic keying (OMU-NRDCSK) is proposed. The chaotic sequence generated at the sending end of the system is used as an information bearing signal after being duplicated, the multi-users’ information modulated by the Walsh codes are transmitted respectively through different delays. At the receiver, after passing through the moving average filter, the received signals are correlated with themselves to demodulate the initial information signals. The bit error rate formula for the system under the Rayleigh fading channel is derived and Monte Carlo simulation is carried out. Analytical and simulation results show that the OMU-NRDCSK system reduces the noise term variance by averaging the received signals and improves the bit error performance, with its transmission rate improved compared to the DCSK system, which effectively improves the bit error performance of the multi-user DCSK system.

    Table and Figures | Reference | Related Articles | Metrics
    Detection method for a dynamic small target using the improved YOLOv3
    CUI Yanpeng,WANG Yuanhao,HU Jianwei
    Journal of Xidian University    2020, 47 (3): 1-7.   DOI: 10.19665/j.issn1001-2400.2020.03.001
    Abstract639)   HTML75)    PDF(pc) (1988KB)(456)       Save

    The visual characteristics of low-altitude drones are less obvious and the scale changes during the detection process. Traditional detection methods are susceptible to interference during detection, and most of those methods cannot work quickly and robustly. To solve this problem, a real-time drone detection algorithm combined with the improved YOLOv3 model and the super resolution method is proposed in this paper. First, frame difference is used to propose the candidate area, and the super-resolution method is used to strengthen the details. Then the dimensional clustering algorithm is used to regenerate the anchors for the model, and the model is slightly adjusted. Finally, we use the improved YOLOv3 to scan both the whole frame and the processed candidate area so as to detect the drones. The frame relationship is also used to implement tracking of drones by real-time detection. With GPU (GTX 1070Ti) acceleration, the method works at a speed of about 20FPS and has an accuracy rate of 96.8% and a recall rate of 95.6%. The results prove that the method can detect drones in different complex backgrounds with a considerable effective detection distance. Compared with the traditional method or normal machine learning method, our method is of a certain theoretical and practical value.

    Table and Figures | Reference | Related Articles | Metrics
    Editorial:Introduction to the special issue on blockchain technology and its progress
    LI Jie,JIA Xiaohua,PEI Qingqi
    Journal of Xidian University    2020, 47 (5): 1-2.   DOI: 10.19665/j.issn1001-2400.2020.05.001
    Abstract461)   HTML140)    PDF(pc) (587KB)(343)       Save
    Reference | Related Articles | Metrics
    Improved face image classification method based on the local embedding network
    LIU Daohua,WANG Shasha,YANG Zhipeng,CUI Yushuang
    Journal of Xidian University    2020, 47 (4): 18-23.   DOI: 10.19665/j.issn1001-2400.2020.04.003
    Abstract332)   HTML53)    PDF(pc) (1374KB)(184)       Save

    In order to improve the accuracy of facial expression recognition and face classification in a local linear embedding network, an improved face image classification method based on the local linear embedding network is proposed. Based on the local linear embedding algorithm, the intra-class to inter-class discrimination matrix is used as the input of the network. At the same time, the reconstruction of the face image set is used to improve the local linear embedding algorithm, and the improvement of the local linear embedding algorithm based on clustering is embedded into the construction process of the convolution kernel, thus increasing the discrimination degree of different types of faces. By the Extended Yale B data set and Olivetti Research Laboratory data set on the contrast experiment, the experiment is analyzed in the treatment of facial expressions and the effects of various methods in the face recognition task, the results show that, compared with the other methods, the recognition rate of the proposed improved locally linear embedding network face image classification method is raised by 11%~26%.

    Table and Figures | Reference | Related Articles | Metrics
    Blockchain radio access network:a new architecture for future mobile communications
    WANG Jiaheng,LE Yuwei,ZHANG Bowen,GUO Ruiwei,GAO Zheng,WANG Ziyue,LING Xintong
    Journal of Xidian University    2020, 47 (5): 3-10.   DOI: 10.19665/j.issn1001-2400.2020.05.002
    Abstract299)   HTML111)    PDF(pc) (2524KB)(194)       Save

    With the rapid development of mobile communications and continuous network expansion, wireless resources become increasingly scarce. Based on the blockchain, the blockchain radio access network (B-RAN) has recently emerged as a promising architecture for the next generation mobile communication system. Via in-depth merging of blockchain and wireless communication technologies, the B-RAN presents a new paradigm to design future mobile networks. This paper briefly introduces the basic concept and workflow of the B-RAN, and provides several technical solutions for the B-RAN in order to satisfy different scenarios and needs. Furthermore, the security performance of the B-RAN is theoretically analyzed. This paper also designs a dedicated framework of the B-RAN and implements its core modules to test its practical performance. The test results show that the B-RAN has a noteworthy advantage in throughput under the scenario of multiple subnetworks. Compared with other blockchain architectures, the B-RAN has a significantly lower latency of service deployment and is able to achieve the balance dynamically between its security level and service latency.

    Table and Figures | Reference | Related Articles | Metrics
    Algorithm for recursive Bayesian localization triggered by temporalseries measurement information
    QIN Ningning,WANG Chao
    Journal of Xidian University    2020, 47 (4): 10-17.   DOI: 10.19665/j.issn1001-2400.2020.04.002
    Abstract286)   HTML51)    PDF(pc) (1445KB)(167)       Save

    To improve the robustness of a position system and reduce the localization error, this paper proposes a fingerprint positioning method based on the recursive Bayesian. To solve the blindness and unreliability of the location fingerprint data in an offline phase, the fingerprint database based on the sample variance is developed to measure the confidence of sampling values and reduce the impact of environmental factors, improving the reliability for online localization. The proposed method provides the target position at the current moment by utilizing the Markov model that is established by the constraint relationship between moments in the source movement, which avoids the jump problem of the position estimation and poor robustness and improves the localization accuracy. Extensive experimental results demonstrate that the average localization error norm of the proposed algorithm is no more than 0.927m, indicating significantly lower errors than other traditional schemes (often by more than 30 percent).

    Table and Figures | Reference | Related Articles | Metrics
    Network security situation adaptive prediction model
    YANG Hongyu,ZHANG Xugao
    Journal of Xidian University    2020, 47 (3): 14-22.   DOI: 10.19665/j.issn1001-2400.2020.03.003
    Abstract217)   HTML27)    PDF(pc) (1380KB)(100)       Save

    Aiming at the low prediction accuracy of traditional network security situation prediction technology, a network security situation adaptive prediction model (NAP) is proposed. First, it extracts alarm elements and calculate network security situation time sequences based on the entropy correlation method. Then, the sequences are taken as the input of the sliding adaptive cubic exponential smoothing method with initial security situation predicted value sequences generated. Finally, the time-varying weighted Markov chain is used to predict the error value based on the error state and the initial predicted values are modified. Experimental results show that the NAP has a better prediction accuracy than other existing models.

    Table and Figures | Reference | Related Articles | Metrics
    Design and optimization of the piezoelectric micromechanical ultrasonic transducer with an AlN thin film
    LOU Lifei,ZHAO Jianxin,LIANG Ya’nan,ZHAO Mingyang,AN Zaifang
    Journal of Xidian University    2020, 47 (3): 8-13.   DOI: 10.19665/j.issn1001-2400.2020.03.002
    Abstract215)   HTML20)    PDF(pc) (1433KB)(76)       Save

    Because existing ultrasonic transducers mostly use PZT and ZnO materials as piezoelectric thin films, while the PZT contains lead and ZnO has the problem of contaminating CMOS manufacturing, a piezoelectric ultrasonic micromechanical transducer with circular bi-laminate bending vibration which uses the aluminium nitride as the piezoelectric layer is designed. The working principle of the transducer is analyzed, the finite element model is established, and the finite element simulation is carried out for the size parameters of the transducer. It is found that the resonant frequency of the transducer is proportional to the thickness of each layer and inversely proportional to the square of the radius of the transducer; when the radius of the upper electrode is about 65% of the radius of the transducer, the resonant amplitude of the transducer is the largest; when the thickness ratio of the silicon and the aluminum nitride of the piezoelectric layer is about 0.6, the resonant amplitude is also the largest. The optimized transducer is simulated and compared with the original model. The results show that the working frequency in air is 9.21MHz, the electromechanical coupling coefficient increases from 21.44% to 27.16% in air and from 3.55% to 11.93% in water. These conclusions provide basic data for the research on the medical imaging probe.

    Table and Figures | Reference | Related Articles | Metrics
    Algorithm for foggy-image pedestrian and vehicle detection
    WANG Yudong,GUO Jichang,WANG Tianbao
    Journal of Xidian University    2020, 47 (4): 70-77.   DOI: 10.19665/j.issn1001-2400.2020.04.010
    Abstract185)   HTML19)    PDF(pc) (2276KB)(111)       Save

    In order to improve the accuracy of the foggy-image pedestrian and vehicle detection, a novel and practical Foggy-image pedestrian and vehicle detection network (FPVDNet) based on the Faster R-CNN is proposed. First, a foggy-density discriminating module (FDM) is proposed to influence the density of the foggy images. In this way, the prediction from the FDM could determine the subsequent operations for different densities of the fog (No-fog, Light fog, and Dense fog). Then, the squeeze and excitation module (SE Module) is designed to use the attention mechanism to improve the feature extraction capability of the network. Meanwhile, the method of the deformable convolution network is applied to add offsets and learn the offsets from target tasks to enhance the transformation modeling capacity of CNNs. Finally, for lack of the annotated fog image dataset, it is necessary to generate a simulated fog image training dataset through the atmospheric scattering model. The simulated foggy image inherits the annotation of the clear image and increases the information on the fog density. Experiments by the proposed FPVDNet are carried out on the 1, 500 real-fog images and 500 real-clear images, with experimental results showing that, compared with the original Faster R-CNN, the mean average detection accuracies are improved 2%~4% by using the FPVDNet.

    Table and Figures | Reference | Related Articles | Metrics
    Datafusion method of multi-sensor target recognition in complex environment
    LU Liping,ZHANG Xiaoqian
    Journal of Xidian University    2020, 47 (4): 31-38.   DOI: 10.19665/j.issn1001-2400.2020.04.005
    Abstract182)   HTML21)    PDF(pc) (1182KB)(81)       Save

    In the complex battlefield environment, the uncertainty of target information causes the target recognition difficulty and misjudgment, which brings about the problem of a low accuracy of target recognition results. This paper proposes a data fusion method for multi-sensor target recognition based on the discrete factor, which can give rise to the output data of the multi-sensor at the multi-period and multi-regions detection, and bring about the discrete factor of obtaining target characteristic corresponding sensors. It can provide the current weight of multi-sensor target recognition according to the discrete factor, establish the relative consistency and the relative weighted consistency function of multi-sensor target recognition, combine the current weight of multi-sensor target recognition and the related consistency function, and construct the data fusion result support calculation model of multi-sensor target recognition. Experimental results show that when the environment is complex, the data fusion method for multi-sensor target recognition based on the discrete factor has more accurate target recognition results, which conforms to the reality in comparison with the data fusion method for target recognition with a given sensor weight in advance. It is shown that the method proposed in this paper is more reliable and has a certain anti-interference ability.

    Table and Figures | Reference | Related Articles | Metrics
    Editorial:introduction to the special issue on network and information security research progress·commemoration of Mr. XIAO Guozhen
    HE Dake,SHEN Bazhong,XING Chaoping,FENG Dengguo,REN Jian,GU Dawu,HU Yupu,ZHANG Yuqing,ZHANG Weiguo
    Journal of Xidian University    2021, 48 (1): 1-6.   DOI: 10.19665/j.issn1001-2400.2021.01.001
    Abstract176)   HTML384)    PDF(pc) (1056KB)(172)       Save
    Reference | Related Articles | Metrics
    Propositional projection temporal logic based distributed model checking method
    SHU Xinfeng,WANG Changtai,WANG Yan,ZHANG Lili
    Journal of Xidian University    2020, 47 (4): 39-47.   DOI: 10.19665/j.issn1001-2400.2020.04.006
    Abstract150)   HTML15)    PDF(pc) (1316KB)(41)       Save

    To alleviate the state-explosion problem of model checking, a novel distributed model checking method based on the propositional projection temporal logic (PPTL). First, the property to be verified in the PPTL formula is transformed into an automaton with the technique of Labeled Normal Form Graph, which in turn is partitioned into multiple subautomata according to the strongly connected components. Then, each subautomaton and the system model in the Hierarchical Syntax Chart are delivered to the members of the verification server cluster, and model checking of the system is implemented in parallel with the on-the-fly technique on multiple computers. Experimental results indicate that, compared with the standalone model checking approach, the proposed method can not only significantly reduce the time consumption but also verify more complex systems.

    Table and Figures | Reference | Related Articles | Metrics
    High performance multiply-accumulator for the convolutional neural networks accelerator
    KONG Xin,CHEN Gang,GONG Guoliang,LU Huaxiang,Mao Wenyu
    Journal of Xidian University    2020, 47 (4): 55-63.   DOI: 10.19665/j.issn1001-2400.2020.04.008
    Abstract147)   HTML27)    PDF(pc) (2691KB)(71)       Save

    The multiply-accumulator (MAC) in existing convolutional neural network(CNN) accelerators generally have some problems, such as a large area, a high power consumption and a long critical path. Aiming at these problems, this paper presents a high-performance MAC based on transmission gates for CNN accelerators. This paper proposes a new data accumulation and compression structure suitable for the MAC, which reduces the hardware overhead. Moreover, we propose a new parallel adder architecture. Compared with the Brent Kung adder, the proposed adder reduces the number of gate delay stages and improves the calculation speed without causing an increase in hardware resources. In addition, we use the advantages of the transmission gate to optimize each unit circuit of the MAC. The 16-by-8 fixed-point high performance MAC based on the methods presented in this paper has a critical path delay of 1.173ns, a layout area of 9049.41μm2, and an average power consumption of 4.153mW at 800MHz under the SMIC 130nm tt corner. Compared with the traditional MAC, the speed is increased by 37.42%, the area is reduced by 47.84%, and the power consumption is reduced by56.77% under the same conditions.

    Table and Figures | Reference | Related Articles | Metrics
    Preliminary research on the blockchain protocol in satellite broadcasting network environment
    ZHANG Yinghao,LIU Xiaofan
    Journal of Xidian University    2020, 47 (5): 11-18.   DOI: 10.19665/j.issn1001-2400.2020.05.003
    Abstract146)   HTML27)    PDF(pc) (1447KB)(91)       Save

    Low throughput has been the biggest obstacle to large-scale blockchain applications. During the past few years, researchers have proposed various schemes for improving the systems’ throughput. However, due to the inherent inefficiency and defects of the Internet, especially in data broadcasting tasks, these efforts have all proved unsatisfactory. In this paper, we propose a novel blockchain protocol which utilizes the satellite broadcasting network instead of the traditional Internet for data broadcasting and consensus tasks. An automatic resumption mechanism is also proposed to solve the unique communication problems of satellite broadcasting. Simulation results show that the proposed algorithm has a lower communication cost and can greatly improve the throughput of the blockchain system. Theoretical estimation of a satellite broadcasting enabled blockchain system’s throughput is 6 000 000 TPS with a satellite bandwidth of 20 Gbps.

    Table and Figures | Reference | Related Articles | Metrics
    Detection of the airborne MIMO radar moving target in the non-Gaussian clutter
    ZHANG Yanfei,SUN Wenjie,SUN Yumei,MENG Xiangwei,CHEN Xiangguang
    Journal of Xidian University    2020, 47 (3): 23-31.   DOI: 10.19665/j.issn1001-2400.2020.03.004
    Abstract145)   HTML15)    PDF(pc) (1308KB)(70)       Save

    Due to the moving platforms, the clutters in distributed airborne MIMO radar are non-Gaussian and non-homogeneous, which leads to having no independent and identically distributed training data to estimate the clutter covariance matrix. To solve the problem, we propose that the covariance of the clutter should be modeled as an inverse complex Wishart distribution whose average value is a Hadamard product of the covariance matrix taper (CMT) and the clutter Doppler spectrum component. Based on this clutter model, a novel detector combing the Bayesian approach and the generalized likelihood ratio test(GLRT) is proposed. Numerical simulation results show that the proposed detector has a better detection performance compared with two current commonly used non-Bayesian detectors.

    Table and Figures | Reference | Related Articles | Metrics
    Novel dual circular polarization planar microstrip slot antenna
    LIU Fan,ZHAO Xiaoyan,ZHAO Hongzhi,JIANG Zhaoneng
    Journal of Xidian University    2020, 47 (3): 86-91.   DOI: 10.19665/j.issn1001-2400.2020.03.012
    Abstract140)   HTML19)    PDF(pc) (2445KB)(60)       Save

    With the rapid development of wireless communication technology, how to use an antenna to realize the function of multiple antennas has become a hot research topic. The double circularly polarized antenna studied in this paper can achieve right-handed circular polarization and left-handed circular polarization in the same frequency band by using a circular annular groove and two orthogonal L-shaped feed lines in the ground plane. At the same time, properly grooving at the center of the ground plane and adding parasitic elements to the front of the L-shaped feed line can change the current on the surface of the feed line and in the ground plane, thereby improving the circular polarization performance of the antenna. Measurement and simulation results show that the impedance bandwidth of the antenna is about 59% (3.13~5.75GHz), and the 3dB axial ratio bandwidth is about 40.5% (3.23~4.87GHz). Also, the isolation between the two ports is higher than 10dB. The results show that the designed antenna has a good performance in both impedance bandwidth and axial ratio bandwidth.

    Table and Figures | Reference | Related Articles | Metrics
    Scheme for miniature time difference measurement with a high resolution and a large range
    QU Bayi,LIU Yehao,ZHANG Taojing,LIU Wei,YU Dongsong,ZHOU Wei
    Journal of Xidian University    2020, 47 (4): 24-30.   DOI: 10.19665/j.issn1001-2400.2020.04.004
    Abstract140)   HTML18)    PDF(pc) (1254KB)(52)       Save

    This paper presents some solutions to the problems in the precise time interval measuring instrument such as the contradiction between high resolution and wide measurement range, the high temperature sensitivity, the low reliability and the big volume and power consumption. The reference signal is used to generate calibration signals to automatically calibrate the analog circuits which are greatly affected by the temperature. The calibration data are used to amend the conversion coefficient between voltage and time interval and the temperature sensitivity of the instrument is greatly reduced. To avoid the gross error in the measurement result caused by the false trigger of the counter, the double counter synchronous measurement technique is adopted and the logic algorithm is used for analyzing and correcting the measured results. Electronic counting method and time-to-voltage converter method are combined together to meet the requirements of the measurement range and resolution of the instrument. The circuit board’s area of the prototype is only 10cm2. The prototype’s effective resolution is above 10ps and the standard deviation of multiple measurement results is below 15ps, the measurement range is wider than 20, 000 seconds, and its measurement results are highly reliable.

    Table and Figures | Reference | Related Articles | Metrics
    Sliding window decoding algorithm for spatially coupled LDPC codes with a variable window
    ZHANG Yamei,ZHOU Lin,CHEN Chen,GUO Rongxin,HE Yucheng
    Journal of Xidian University    2020, 47 (3): 128-134.   DOI: 10.19665/j.issn1001-2400.2020.03.018
    Abstract132)   HTML19)    PDF(pc) (1343KB)(42)       Save

    Spatially coupled low density parity check (SC-LDPC) codes can achieve a better decoding performance with a small message recovery latency due to the sliding window decoding. An improved decoding scheme based on window extension is proposed for further enhancing the performance of the sliding window decoding. In contrast to conventional sliding window decoding, the window size of this scheme can vary according to the average logarithmic likelihood ratio (LLR) value of the target symbol. Specifically, for every iteration in the decoding process, we compare the average LLR value of the target symbol with the preset threshold. If the average LLR value of the target symbol is less than the preset threshold and the current window size does not exceed the maximum size, the decoding window size adds one and then performs a new iteration with the new window size. By this means, the scheme can achieve trade-off between decoding performance, complexity and latency. Simulation results on the additive white Gaussian noise (AWGN) channel show that this scheme can significantly improve the sliding window decoding performance of SC-LDPC codes.

    Table and Figures | Reference | Related Articles | Metrics
    Improved Siamese network based object tracking combined with the deep contour feature
    YU Zhichao,ZHANG Ruihong
    Journal of Xidian University    2020, 47 (3): 40-49.   DOI: 10.19665/j.issn1001-2400.2020.03.006
    Abstract130)   HTML16)    PDF(pc) (3638KB)(55)       Save

    The existing Siamese object tracking algorithms easily lead to tracking drift under the influence of object deformation and occlusion, this paper proposes an improved object tracking algorithm based on deep contour extraction networks to achieve stable detection and tracking of any object under complex backgrounds. First, the contour detection network automatically obtains the closed contour information on the object and uses the flood-filling clustering algorithm to obtain the contour template. Then, the contour template and the search area are input into the improved Siamese network so as to obtain the optimal tracking score value and adaptively update the contour template. If the object is fully obscured or lost, the Yolov3 network is used to search the object in the entire field of view to achieve stable tracking throughout the process. A large number of qualitative and quantitative simulation results show that the improved model can not only improve the object tracking performance under complex backgrounds, but also improve the response time of airborne systems, which is suitable for engineering applications.

    Table and Figures | Reference | Related Articles | Metrics
    3D model recognition and segmentation based on multi-feature fusion
    DANG Jisheng,YANG Jun
    Journal of Xidian University    2020, 47 (4): 149-157.   DOI: 10.19665/j.issn1001-2400.2020.04.020
    Abstract126)   HTML19)    PDF(pc) (3399KB)(52)       Save

    Current methods focusing on 3D model recognition and segmentation have to some extent ignored the relationship between the high-level global single-point features and the low-level local geometric features of those models, resulting in poor recognition results. A multi-feature fusion approach which takes into consideration the aforementioned ignored relationship is proposed. First, a global single-point network is established to extract the global single-point features with high-level semantic recognition ability by increasing both the width of convolution kernel and the depth of the network. Second, an attentional fusion layer is constructed to learn the implicit relationship between global single-point features and local geometric features to fully explore the fine-grained geometric features that can better represent model categories. Finally, the global single-point features and fine-grained geometric features are further fused to achieve the complementation of advantages and enhance the feature richness. Experimental verification is carried out on the 3D model recognition datasets ModelNet40, ModelNet10 and segmentation datasets ShapeNet Parts, S3DIS, vKITTI, respectively, and comparison with current mainstream recognition algorithms shows that the proposed algorithm not only has higher recognition and segmentation accuracy, but also has stronger robustness.

    Table and Figures | Reference | Related Articles | Metrics
    A new method for white-box implementation of CLEFIA algorithm
    YAO Si,CHEN Jie,GONG Yating,XU Dong
    Journal of Xidian University    2020, 47 (5): 150-158.   DOI: 10.19665/j.issn1001-2400.2020.05.020
    Abstract126)   HTML18)    PDF(pc) (960KB)(48)       Save

    Considering the shortcomings of the white-box CLEFIA algorithm (Su-white-box CLEFIA algorithm) implemented by Su Shuai et al with perturbations technology, the analytical method of Michiels et al can recover the master key in a time complexity of no more than 2.5×229. In order to ensure that the CLEFIA algorithm runs safely in a white-box attack context, a white-box implementation scheme (new white-box CLEFIA algorithm) based on the lookup table technology is proposed, which requires 36.034MB of memory space. The white-box diversity values corresponding to the two types of lookup tables in this scheme are 2829 and 2813, respectively, and the time complexity for the affine equivalent algorithm can reach O(276). This scheme can effectively resist code extraction attacks, key extraction attacks, attacks by Michiels et al and analysis by De Mulder.

    Table and Figures | Reference | Related Articles | Metrics
    Using Monero to realize covert communication
    LAN Yiqin,ZHANG Fangguo,TIAN Haibo
    Journal of Xidian University    2020, 47 (5): 19-27.   DOI: 10.19665/j.issn1001-2400.2020.05.004
    Abstract125)   HTML14)    PDF(pc) (1272KB)(79)       Save

    The development of traffic analysis technology makes many covert communication methods based on the TCP/IP architecture face many threats. The subliminal channel is one that can realize covert communication by using cryptographic systems such as digital signatures and authentication. During the digital signature process, both parties of the communication can transmit secret information, and no one except the two parties knows the existence of the secret information. As a new generation technology, the blockchain adopts a distributed structure, and its openness, data tampering and security make it an effective carrier for constructing subliminal channels. This article introduces Monero, a new type of digital currency that uses blockchain technology, and constructs two subliminal channels in Monero. The first is based on the sharing of keys between signers and verifiers. The second does not share keys. Covert communication is achieved through these two subliminal channels.

    Table and Figures | Reference | Related Articles | Metrics
    Health prediction algorithm for edge layer nodes
    SUN Qian,ZHANG Jiarui,GAO Ling,WANG Yuxiang,YANG Jianfeng
    Journal of Xidian University    2020, 47 (3): 32-39.   DOI: 10.19665/j.issn1001-2400.2020.03.005
    Abstract123)   HTML12)    PDF(pc) (1284KB)(38)       Save

    An improved state prediction algorithm for edge layer nodes is proposed to solve the problem of the existing state prediction algorithm for edge layer nodes based on Hidden Markov, such as the subjectivity of initial parameter selection, the dependence of feature weights setting on experience, and the bad adaptability of multidimension feature node analysis. At the data processing layer of the algorithm, the parameter of the model and observation sequence are optimized by the method of clustering; and then at the training layer of the algorithm, the single-feature Hidden Markov Model is used to model the multi-feature Hidden Markov Model; finally, an adaptive genetic algorithm based on the information gain is used to optimize and reduce the state sequence generated by the Hidden Markov Model. The problems of feature weight setting and parameter initial value selection are solved effectively. Experimental results show that the proposed algorithm effectively improves the accuracy of the high-dimensional health state of large-scale edge layer nodes compared with the existing algorithms.

    Table and Figures | Reference | Related Articles | Metrics
    Contour reconstruction method for noisy image based on depth residual learning
    WANG Xiaoming,ZHANG Shuyan,ZHANG Jie,YUAN Sicong
    Journal of Xidian University    2020, 47 (3): 66-71.   DOI: 10.19665/j.issn1001-2400.2020.03.009
    Abstract122)   HTML13)    PDF(pc) (1381KB)(53)       Save

    In order to improve the recognition ability of noisy images, a method of contour reconstruction based on depth residuals learning is proposed. The sharpening template matching technique is used to enhance the noisy image information, the local gray level information on the image is used to construct the edge active contour model of the image, and the active contour lasso method is used to reconstruct the image with a high resolution. The feature quantities of local gray energy and local gradient energy of the noisy image are extracted, and a convolutional neural network classifier is constructed to classify the features. The learning depth of the learning convolutional neural network is judged by combining the similarity of the gray histogram of the image. The resolution ability of image detail information is improved, and the contour high resolution reconstruction of the noisy image is realized. Simulation results show that the proposed method has a high resolution and a high peak signal to noise ratio (PSNR), which improves the recognition ability of the image effectively.

    Table and Figures | Reference | Related Articles | Metrics
    Algorithm for encrypted search with forward secure updates and verification
    LI Han,ZHANG Chen,HUANG Hejiao,GUO Yu
    Journal of Xidian University    2020, 47 (5): 48-56.   DOI: 10.19665/j.issn1001-2400.2020.05.007
    Abstract121)   HTML13)    PDF(pc) (1178KB)(61)       Save

    Recent advances in cloud computing are further pushing forward the development of the technique known as searchable encryption. However, existing encrypted search schemes mainly consider a centralized setting, where a search is conducted in a traditional client-server model. How to apply searchable encryption schemes to an untrusted distributed setting like the blockchain environment remains to be explored. Meanwhile, the advanced security property like forward security is posing new challenges that traditional technologies are no longer sufficient to cope with. In this work, we explore the potential of the blockchain technique and propose a novel dual index structure for forward-secure encrypted search with dynamic file updates. We show how to synthesize this design strategy in the context of blockchain-based storage systems and achieve both optimal search and update complexity. We also propose a verification scheme to verify the correctness of search results and customize an encrypted on-chain checklist to achieve strong data protection and lower the blockchain overhead. We implement the prototype on a Redis cluster and conduct performance evaluations on the Amazon Cloud. Extensive experiments demonstrate the security and efficiency of the design.

    Table and Figures | Reference | Related Articles | Metrics
    Transmission synthesis scheme for a multicast system with unknown locations of eavesdroppers
    GAO Jianbang,YUAN Zhaohui,ZHOU Jing
    Journal of Xidian University    2020, 47 (5): 144-149.   DOI: 10.19665/j.issn1001-2400.2020.05.019
    Abstract120)   HTML18)    PDF(pc) (2104KB)(32)       Save

    In order to solve the problem of multicast wireless secure communication with unknown locations of the eavesdroppers, a secure communication synthesis scheme was proposed based on the frequency diverse arrays. By studying the frequency diverse arrays model and analyzing the beam pattern, a random frequency diverse array is constructed at the transmitter. At the same time, combined with the added artificial noise baseband signal processing method, the maximizing artificial noise energy method is designed to optimize the beamforming weighted vector of each multicast group, so as to improve the security performance of the multicast system. Numerical results show that the scheme realizes secure communication of a multicast system and can precisely control the signal energy received by legitimate users.

    Table and Figures | Reference | Related Articles | Metrics
    Dynamic inference method for the orbit status of space objects
    LU Wanjie,LAN Chaozhen,LV Liang,SHI Qunshan,XU Qing
    Journal of Xidian University    2020, 47 (3): 72-79.   DOI: 10.19665/j.issn1001-2400.2020.03.010
    Abstract120)   HTML4)    PDF(pc) (1258KB)(17)       Save

    Aiming at the uncertainty of the orbit status of non-cooperative space objects, a dynamic inference method for the orbit status of space objects based on dynamic Bayesian networks is proposed. First, the semantic model for the orbit status of space objects is established, and the semantic relationships such as the orbit status, orbit class and orbit change are explained. Second, the orbit status characteristics are analyzed, and the hierarchical division method for coplanar and noncoplanar orbit change is constructed. Then, based on the dynamic Bayesian network, an inference method for the orbit status of space objects is established, and the relationships between orbit status, orbit class, and orbit change are used to obtain the dynamic change process of the orbit status. Finally, the proposed method is validated by comparing with actual situations of space objects of different orbital classes. Experimental results demonstrate that the proposed dynamic inference method for the orbit status of space objects can inference the orbit status with uncertainty and obtain the change process, which provides support and assistance for further decision-making.

    Table and Figures | Reference | Related Articles | Metrics
    Model predictive path integral method for nonlinear random vibration control
    GUO Kongming,JIANG Jun,XU Yalan
    Journal of Xidian University    2020, 47 (4): 48-54.   DOI: 10.19665/j.issn1001-2400.2020.04.007
    Abstract111)   HTML7)    PDF(pc) (1307KB)(35)       Save

    In order to find a way to transfer back the state of a nonlinear random vibration system which is far away from the trivial equilibrium point, a model predictive path integral control method is introduced. Under certain conditions, the Hamilton-Jacobi-Bellman equation for optimal control of nonlinear random vibration can be linearized by exponential transformation. Based on the Feynman-Kac theorem, the path integral method can be used to solve the optimal control force. By introducing the idea of model predictive control, the control force can be updated in real time according to the actual state of the system. Numerical simulation is carried out for the control of two typical systems, van der Pol equation and Duffing equation. The results show that the state of the system can be quickly transferred to the vicinity of the ordinary equilibrium point, while the control force and real-time cost decreases monotonically after the initial fluctuation. Therefore, the model predictive control path integration method can be well applied to the vibration of random nonlinear systems far from the trivial equilibrium point.

    Table and Figures | Reference | Related Articles | Metrics
    Genomic data privacy-preserving scheme based on the improved PSI protocol
    TIAN Meijin,MA Jianfeng,LIU Zhiquan,FENG Bingwen,WEI Kaimin
    Journal of Xidian University    2020, 47 (4): 94-101.   DOI: 10.19665/j.issn1001-2400.2020.04.013
    Abstract110)   HTML5)    PDF(pc) (1332KB)(32)       Save

    In order to solve the problem of privacy leakage in the sharing of genomic data, a genomic data privacy-preserving scheme based on the improved Private Set Intersection (PSI) computing protocol is presented, which leverages the Bloom Filter, Cuckoo Hash, and Random Oblivious Transfer (ROT) extension protocol to not only protect the genomic sequence information on the user when detecting a disease-causing gene but also judge whether he or she has some disease factors or not. Moreover, the correctness and security of the proposed scheme in the detection scenario of disease-causing genes are proved in the semi-honest security model. In addition, a series of experiments is conducted to verify the efficiency of the proposed scheme. The results reveal that the running time and communication overhead of the proposed scheme are much less than those of the existing PSI schemes.

    Table and Figures | Reference | Related Articles | Metrics
    Research on key technology of blockchain privacy protection and scalability
    WANG Hui,WANG Licheng,BAI Xue,LIU Qinghua,SHEN Xiaoying
    Journal of Xidian University    2020, 47 (5): 28-39.   DOI: 10.19665/j.issn1001-2400.2020.05.005
    Abstract109)   HTML13)    PDF(pc) (1435KB)(69)       Save

    The blockchain has typical features such as decentralization of accounts, data irrevocability and transparency of information, which solves to a certain extent the collaboration and value flow between individuals who do not trust each other. However, the public verifiability of the blockchain poses security challenges for user privacy, while its performance issues, especially in terms of transaction throughput and scalability, also limit further development of blockchain technology. This paper researches and discusses the two major aspects of blockchain privacy protection and scaling technologies. First, it outlines the Bitcoin and ETH technologies in the blockchain and the comparison between them; then, it introduces several typical blockchain-oriented key technologies and development status of privacy protection such as ring signature, zero knowledge proof, secure multi-party computing, homomorphic commitment and subvector commitment. Similarly, the key technologies and case studies of blockchain scale-up are introduced from both up and down the chain to break through the two major bottlenecks in the development of blockchain privacy protection and scalability, so that the blockchain has a smart contract function, under the premise of protecting user privacy with high transaction throughput and scalability, to meet the actual needs of a wide range of fields such as finance, education, social management and industrial logistics, is the future direction of development of the blockchain.

    Table and Figures | Reference | Related Articles | Metrics
    Low complexity probability-based piecewise linear approximation of the sigmoid function
    NGUYEN Van-Truong,CAI Jueping,WEI Linyu,CHU Jie
    Journal of Xidian University    2020, 47 (3): 58-65.   DOI: 10.19665/j.issn1001-2400.2020.03.008
    Abstract108)   HTML10)    PDF(pc) (1349KB)(27)       Save

    In order to improve the network recognition accuracy in the low complexity condition, a piecewise linear sigmoid function approximation based on the distribution probability of the neurons’ values is proposed only with one addition circuit. The sigmoid function is first divided into three fixed regions. Second, according to the neurons’ values distribution probability, the curve in each region is segmented into sub-regions to reduce the approximation error and improve the recognition accuracy. The slope of the piecewise linear function is set as 2-n, effectively reducing the hardware implementation complexity. Experiments performed on Xilinx’s FPGA-XC7A200T implement the MNIST handwritten digits recognition. The results show that the proposed method achieves a 97.45% recognition accuracy in a deep neural network and 98.42% in a convolutional neural network, up to 0.84% and 0.57% higher than other approximation methods only with one addition circuit.

    Table and Figures | Reference | Related Articles | Metrics
    Research and experiment on multi-user computational offloading based on mobile edge computing
    LU Jixiang,FANG Boya
    Journal of Xidian University    2020, 47 (4): 78-85.   DOI: 10.19665/j.issn1001-2400.2020.04.011
    Abstract105)   HTML5)    PDF(pc) (1402KB)(34)       Save

    The fundamental problem of multi-user computation offloading for Mobile Edge Computing is investigated in heterogeneous overlay networks where each user can connect and offload its computing workloads to multiple heterogeneous wireless access points in parallel. The problem of average user overhead minimization with the delay constraint is formulated to obtain the optimal strategy of workload partition and heterogeneous resource allocation. A successive convex approximation (SCA) based algorithm is finally developed, which addresses the problem of non-convex optimization by iteratively solving a sequence of separable strongly convex problems. Numerical results are presented to prove that the proposed offloading mechanism can effectively reduce the service latency and energy consumption of users compared with the conventional non-cooperative approach.

    Table and Figures | Reference | Related Articles | Metrics
    Improved scheme for spectrum allocation in cognitive wireless sensor networks
    ZHOU Ji,XU Mengying,WANG Jiaojiao,LU Yi
    Journal of Xidian University    2020, 47 (3): 80-85.   DOI: 10.19665/j.issn1001-2400.2020.03.011
    Abstract104)   HTML5)    PDF(pc) (1175KB)(37)       Save

    In order to effectively allocate the idle spectrum and improve spectrum utilization of cognitive wireless sensor networks, it is necessary to design an efficient spectrum allocation algorithm. Aiming at the problem of spectrum allocation in cognitive wireless sensor networks, an improved method for spectrum allocation is suggested. A new chaotic dynamic clonal evolution algorithm is designed. Then the graph theory coloring model is established with the corresponding fitness function derived. Traditional evolutionary algorithms have the problem of premature convergence, so chaotic operators, adaptive operators and cloning operators are added to the traditional evolutionary algorithms to accelerate the convergence of the algorithm. The chaotic dynamic clonal evolutionary algorithm is compared with the simulated annealing algorithm and the ant colony algorithm by simulation. The simulation results show that compared with the ant colony algorithm and the simulated annealing algorithm, the chaotic dynamic clonal evolution algorithm can effectively improve the global search ability, and significantly improve the network benefit value of spectrum allocation. The results also show that the proposed chaotic dynamic clonal evolution algorithm can make full use of existing spectrum resources and improve the system throughput.

    Table and Figures | Reference | Related Articles | Metrics
    Polar coded non-orthogonal multiple access to 6G wireless systems
    NIU Kai,XU Wenjun,ZHANG Ping
    Journal of Xidian University    2020, 47 (6): 5-12.   DOI: 10.19665/j.issn1001-2400.2020.06.002
    Abstract100)   HTML9)    PDF(pc) (1351KB)(29)       Save

    As the first type of channel codes which has achieved the channel capacity, polar codes are an important candidate for the 6G data transmission. A polar coded framework of the non-orthogonal multiple access (NOMA) to the 6G system is proposed. In this framework, the scheme for the polar coded coordinated NOMA is investigated to fulfill the requirement of high-capacity transmission of 6G systems. Furthermore, the scheme for the polar coded non-coordinated NOMA can achieve the ultra-high reliable access to the 6G internet scenario. All these schemes indicate that polar coded NOMA techniques can dramatically boost the performance of 6G wireless transmission and has a broad application prospect.

    Table and Figures | Reference | Related Articles | Metrics
    On the significance and function of the Xiao-Massey theorem
    FENG Dengguo
    Journal of Xidian University    2021, 48 (1): 7-13.   DOI: 10.19665/j.issn1001-2400.2021.01.002
    Abstract100)   HTML14)    PDF(pc) (669KB)(53)       Save

    Divide-and-conquer correlation analysis is an important stream cipher analytical method,which is one of the analytical methods that must be defended when designing the stream cipher.The frequently-used defense strategy is to make the cryptographic function used in the stream cipher have a certain correlation immune order.This kind of cryptographic function is called the correlation immune function.The characterization of correlation immune functions is the theoretical basis for constructing and analyzing such functions.Professor G.Z.Xiao and Professor J.L.Massey first gave the characterization of the Walsh spectrum of correlation immune Boolean functions (called Xiao-Massey theorem),which opened up a new research direction for the study of stream ciphers.This paper mainly reviews the Xiao-Massey theorem,sketches the significance of the Xiao-Massey theorem,and explains the function of the Xiao-Massey theorem.

    Reference | Related Articles | Metrics
    Phased smoke detection algorithm using dual network fusion
    DU Lizhao,XU Yan,ZHANG Wei
    Journal of Xidian University    2020, 47 (4): 141-148.   DOI: 10.19665/j.issn1001-2400.2020.04.019
    Abstract99)   HTML7)    PDF(pc) (3526KB)(43)       Save

    Existing video smoke detection methods have a low detection accuracy in complex scenes and cannot detect smoke areas in video frames accurately. In this paper, a phased smoke detection algorithm that combines the smoke movement process and the target detection algorithm is proposed. First, an improved ViBe algorithm based on smoke color features is used to extract the continuously moving smoke in video. Then, the YOLO v3 model is used as the target detection network. The channel attention mechanism is added to the residual structure of its backbone network. Focal-loss and GIoU are utilized to improve the loss function. According to the test of the smoke image data set, the detection time of the improved network on a single picture is 38.4ms and the mAP reaches 92.13%, which is 2.19% higher than that by the original model. While extracting smoke motion, the same frame is sent to the improved YOLO v3 for smoke detection. Finally, comprehensive discrimination is made based on the smoke detection results in stages. Public smoke video test results show that the algorithm has an average detection rate of 98.88%, which proves that the algorithm has a strong adaptability, a high detection efficiency in complex scenes and a high practical application value.

    Table and Figures | Reference | Related Articles | Metrics
    Fast design method for the high-performance dual-passband filter
    XU Tongtong,XIANG Zheng
    Journal of Xidian University    2020, 47 (5): 130-136.   DOI: 10.19665/j.issn1001-2400.2020.05.017
    Abstract97)   HTML12)    PDF(pc) (1930KB)(42)       Save

    In this paper, in order to improve the efficiency of designing the dual-passband filter, the extraction method of the coupling matrix of the dual-passband filter is studied based on the duplexer theory, and a dual-passband cavity filter is designed. First, the basic theory of the coupling matrix is analyzed, and then the method for extracting the coupling matrix based on the duplexer is studied. Finally, the corresponding coupling matrix is verified theoretically by the circuit model, and the design and simulation of the filter are performed using electromagnetic simulation software. The simulation results show that the dual-passband filter designed in this paper has the characteristics of a flexible and controllable passband, a low insertion loss, and good out-of-band rejection. The proposed method can improve the efficiency of designing the dual-passband filter.

    Table and Figures | Reference | Related Articles | Metrics
    Mechanism for proof-of-reputation consensus for blockchain validator nodes
    LIU Naian,CHEN Zhihao,LIU Guokun,LI Yang
    Journal of Xidian University    2020, 47 (5): 57-62.   DOI: 10.19665/j.issn1001-2400.2020.05.008
    Abstract94)   HTML11)    PDF(pc) (772KB)(33)       Save

    A mechanism for proof-of-reputation consensus for blockchain validator nodes is proposed to deal with existing blockchain consensus mechanism's lack of evaluation of validator node's reputation and the inability to effectively prevent Byzantine behaviors. First, an interactive indicator is designed for validator nodes to represent their contribution in the blockchain network, which will be used as the reputation benchmark of validator nodes. Second, another reliability indicator is designed for validator nodes from the aspects of online time and the number of valid blocks, which will be used as the weight of the reputation improvement of validator nodes. Finally, the reputation of validator nodes of the current round is comprehensively calculated, and a set of producing validators of the current round is selected based on the reputation ranking. Experimental results show that the proof of reputation consensus mechanism has certain advantages in dealing with malicious and lazy behaviors, and that it can also reduce the impact of capital and energy consumption on the blockchain consensus mechanism while ensuring the validity of the credit evaluation.

    Table and Figures | Reference | Related Articles | Metrics
    Scheme for being able to regulate a digital currency with user privacy protection
    TIAN Haibo,LIN Huizhi,LUO Peiran,SU Yinxue
    Journal of Xidian University    2020, 47 (5): 40-47.   DOI: 10.19665/j.issn1001-2400.2020.05.006
    Abstract92)   HTML8)    PDF(pc) (958KB)(37)       Save

    The regulation of digital currency is currently a hot topic. At present, there are some digital currencies that protect user privacy well, but are unable to be regulated, which hinders the further application of these digital currencies. By taking Monero as an example, this paper proposes an improved solution based on a group signature and a knowledge proof for CryptoNote, the underlying technology of Monero, which can achieve the regulation of Monero. The group manager can trace a suspected transaction, determine the real identity of its sender, find the complete transaction list of the sender, and revoke the private key to freeze the coins of the sender when necessary.

    Table and Figures | Reference | Related Articles | Metrics
    Deep learning model for micro-motion classification of cone targets
    LI Jiang,FENG Cunqian,WANG Yizhe,XU Xuguang
    Journal of Xidian University    2020, 47 (3): 105-112.   DOI: 10.19665/j.issn1001-2400.2020.03.015
    Abstract88)   HTML4)    PDF(pc) (2069KB)(22)       Save

    To overcome the shortcomings of traditional micro-motion classification of spatial cone targets, such as manual construction, feature extraction, and lack of generality, intelligence and poor classification performance under strong noise, a new network model combining a convolutional neural network and a bidirectional long short-term memory network is proposed. The network combines the residual network, inception network and bidirectional long short-term memory network into an integrated network. By increasing the depth and width of the network to mine the abstract features of higher dimensions, the classification accuracy of the network can be improved. The reasoning ability of the bidirectional long short-term memory network can improve the fault tolerance of the network, and the advantages of time series classification and the jumping bypass branch structure of the residual network can also reduce parameter redundancy and speed up network training. Simulation results show that the network model not only achieves faster intelligent classification, but also improves the accuracy of ResNet-18 and GoogLeNet models by 5% and 4% respectively, thus verifying the validity and generalization ability of the model.

    Table and Figures | Reference | Related Articles | Metrics
    Temperature and humidity sensor using the multimode fiber cascaded Bragg grating
    LIU Xin,LI Jinze,SUN Hao
    Journal of Xidian University    2020, 47 (3): 92-96.   DOI: 10.19665/j.issn1001-2400.2020.03.013
    Abstract88)   HTML7)    PDF(pc) (1492KB)(14)       Save

    In order to design an optical fiber sensor with a simple structure which can simultaneously measure temperature and relative humidity, we use the multimode fiber cascade Bragg grating to form the basic structure of the sensor. First, a 6mm multimode fiber is connected to a Bragg grating. Then the diameter of the multimode fiber is etched to 40μm by hydrofluoric acid. Finally, a layer of carboxymethyl cellulose hydrogel is coated on the multimode fiber. The temperature and humidity response of the fabricated optical fiber sensor is tested. Experimental results show that the designed sensor has a humidity sensitivity of 69.6pm/% RH and a temperature sensitivity of 15pm/℃. The designed sensor is very sensitive to temperature and humidity, and has a good application prospect.

    Table and Figures | Reference | Related Articles | Metrics
    Approximate computing method based on cross-layer dynamic precision scaling for the k-means
    LI Zhao,YUAN Wenhao,REN Chongguang,HUANG Chengcheng,DONG Xiaoxiao
    Journal of Xidian University    2020, 47 (3): 50-57.   DOI: 10.19665/j.issn1001-2400.2020.03.007
    Abstract85)   HTML6)    PDF(pc) (1293KB)(34)       Save

    With the application of artificial intelligence on the embedded platform, the k-means clustering algorithm, as the basis of the artificial intelligence method, is implemented on the embedded platform. Energy consumption is the key for the algorithm implementation on the embedded platform. In order to reduce the energy consumption of the k-means on the embedded platform, an approximate computing method based on cross-layer dynamic precision scaling for the k-means is proposed. First, the iteration process is constrained from the distance between data point to centroid and data point change trend. And a dynamic precision scaling method is proposed. Then the data reorganization and access method of external memory is designed from the structural level, which can realize the access of approximate memory. In addition, the approximate adder and multiplier are designed which can automatically adjust the calculation accuracy. Finally, the approximate computing of the k-means is realized. Experimental results show that the proposed method can reduce the energy consumption by 55%~58% compared with the accurate computing without affecting the quality of clustering. The proportion of the energy saving is the highest.

    Table and Figures | Reference | Related Articles | Metrics
    GLMB extended target tracking based on one-step data association
    LI Cuiyun,LI Yang,JI Hongbing,SHI Renzheng
    Journal of Xidian University    2020, 47 (5): 137-143.   DOI: 10.19665/j.issn1001-2400.2020.05.018
    Abstract85)   HTML6)    PDF(pc) (2048KB)(29)       Save

    Due to the inseparability of measurements in neighborhood scenarios, the tracking performance of the traditional extended target tracking algorithm would degrade. In this paper, a new extended target tracking algorithm based on one step data association is proposed to solve the problem. First, the algorithm models the target with a multiplicative noise model. And then, the one step data association method in the Joint Probabilistic Data Association (JPDA) theory is combined with a Generalized Labeled Multi-Bernoulli (GLMB) filter. Simulation results show that the algorithm can track the target in cross and neighborhood scenarios effectively and that it is superior to the traditional extended target tracking algorithms based on measurement partition in estimation accuracy.

    Table and Figures | Reference | Related Articles | Metrics
    Propagation properties of a non-canonical vortex beam in a high numerical aperture system
    LI Jinhong,PANG Xiaoyan,FENG Chen
    Journal of Xidian University    2020, 47 (4): 102-108.   DOI: 10.19665/j.issn1001-2400.2020.04.014
    Abstract84)   HTML2)    PDF(pc) (2568KB)(26)       Save

    A non-canonical vortex is an optical helical phase structure with the same topological charge of a canonical vortex but different phase distributions. Based on the Richards&Wolf vectorial diffraction theory, the expression for the strongly focused, linearly polarized non-canonical vortex beam is derived, and its propagation properties are studied numerically in the focal region. It is that the transverse focal shift does not only occur in the strongly focused, off-axis (or on-axis) canonical vortex beams, but also can be seen in a strongly focused, non-canonical vortex beam. The transverse focal shift in these two fields have the same form, but the factors influencing them are quite different. It is also demonstrated that because of the transverse focal shift, if both the semi-aperture angle and the phase distribution factor meet a certain requirement, the total field intensity pattern in the focus region can rotate clockwise in the propagation direction, while the intensity maxima will also rotate 180° from the negative half space to the positive half space. The result will provide a new way for controlling the field distribution in structured fields, which may be applied in optical tweezers.

    Table and Figures | Reference | Related Articles | Metrics
    Rule-based automatic program repair method
    HUANG Yuming,MA Jianfeng,LIU Zhiquan,FENG Bingwen,WEI Kaimin
    Journal of Xidian University    2020, 47 (4): 117-123.   DOI: 10.19665/j.issn1001-2400.2020.04.016
    Abstract84)   HTML6)    PDF(pc) (1299KB)(29)       Save

    To tackle the problem of a low accuracy of test suite-based automatic program repair methods, this paper proposes a rule-based automatic program repair method named RuleFix. The proposed method first mines implicit programming rules in programs to locate defects, and then selects an appropriate patch according to the implicit programming rules, and lastly verifies the patch by utilizing the program synthesis tool to ensure the correctness of the repair result. Moreover, to tackle the problem that the existing rule mining algorithms cannot effectively mine low-frequency rules, a low-frequency rule mining algorithm is proposed, which can derives new rules based on the existing rules to improve the ability of rule mining. Finally, a prototype tool is implemented based on the proposed method, and then the proposed method is compared with the existing automatic program repair methods. Experimental results demonstrate that the proposed method has a significantly higher repair rate and accuracy rate than the existing GenProg and PAR methods.

    Table and Figures | Reference | Related Articles | Metrics
    Optimization of the voltage regulators and voltage noise for the power delivery network
    WANG Lu,WANG Leilei
    Journal of Xidian University    2020, 47 (4): 124-131.   DOI: 10.19665/j.issn1001-2400.2020.04.017
    Abstract82)   HTML2)    PDF(pc) (1259KB)(21)       Save

    In order to reduce both the power loss of the switched capacitor converter integrated in the on-chip power delivery network and the voltage noise at the load, this paper proposes an optimization method to optimize the capacitance allocation between the flying capacitors of the switched-capacitor converter (SCCs) and the decoupling capacitors at the load. By formulating and solving the inequality-constrained nonlinear programming problem, the SCCs’ flying capacitance and decoupling capacitance can be optimally allocated and the sum of power loss and voltage noise is effectively reduced. Experimental results show that the joint optimization of the SCCs’ capacitance and decoupling capacitance can reduce the sum of power loss and voltage noise by about 11%~28%. For larger power deliver networks, this method can efficiently reduce the power loss and voltage noise.

    Table and Figures | Reference | Related Articles | Metrics
    Model of abstractive text summarization for topic-aware communicating agents
    ZHANG Zheming,REN Shuxia,GUO Kaijie
    Journal of Xidian University    2020, 47 (3): 97-104.   DOI: 10.19665/j.issn1001-2400.2020.03.014
    Abstract81)   HTML12)    PDF(pc) (1231KB)(21)       Save

    To solve the problem that the traditional automatic text summary model cannot generate a high-quality long text summary due to the limitation of the length of the RNN (Recurrent Neural Network), a model of abstractive text summarization for topic-aware communicating agents has been proposed. First, the problem that the LSTM (Long Short-Term Memory) input sequence is too long to generate the abstract with prior information has been solved by dividing the encoder into multiple collaborating agents. Then for providing topic information and improving the correlation between the generated abstract and the source text, the joint attention mechanism has been added into our model. Finally, a hybrid training method with reinforcement learning has been employed in order to solve the problem of exposure bias, and optimize the evaluation index directly. The results show that our model not only generate long text summaries with prominent themes, but also has a higher score than the state-of-the-art models, which indicates that with the help of topic information, the model for communicating agents can be expected to generate long text summaries better.

    Table and Figures | Reference | Related Articles | Metrics
    Editorial:Introduction to the special issue on information transmission and access technologies for B5G/6G
    BAI Baoming,MA Xiao,CHEN Wen,ZHANG Zhaoyang
    Journal of Xidian University    2020, 47 (6): 1-4.   DOI: 10.19665/j.issn1001-2400.2020.06.001
    Abstract81)   HTML21)    PDF(pc) (737KB)(78)       Save
    Reference | Related Articles | Metrics
    Constellation splitting security transmission technology based on the multi-parameter weighted-type fractional Fourier transform for dual-polarized satellites
    WANG Haobo,DA Xinyu,XU Ruiyang,LIANG Yuan,NI Lei,ZHANG Hongwei
    Journal of Xidian University    2020, 47 (3): 121-127.   DOI: 10.19665/j.issn1001-2400.2020.03.017
    Abstract79)   HTML8)    PDF(pc) (1643KB)(19)       Save

    In order to improve the security transmission performance of dual-polarized satellites, a constellation splitting security transmission system based on the multi-parameter weighted-type Fractional Fourier Transform (MP-WFRFT) is proposed. By analyzing the time-frequency characteristics of signals, the constellation splitting function is constructed and solved by the Genetic Algorithm (GA). The constellation splitting criteria of the MP-WFRFT in the two-dimensional surface and three-dimensional sphere are mainly explored. Simulation results show that the splitting pattern is determined by the ratio of time-domain terms on the MP-WFRFT and the transmitting signal can be camouflaged by setting different time-domain terms ratio constrains to prevent the eavesdropper from acquiring the correct message. The error in the transform parameter can improve the security performance. The larger the parameter error of the MP-WFRFT is, the higher secrecy capacity can be achieved, which verifies the rationality and effectiveness of the proposed scheme.

    Table and Figures | Reference | Related Articles | Metrics
    Waveletdomain dilated network for fast low-dose CT image reconstruction
    LI Kunlun,ZHANG Lu,XU Hongke,SONG Huansheng
    Journal of Xidian University    2020, 47 (4): 86-93.   DOI: 10.19665/j.issn1001-2400.2020.04.012
    Abstract79)   HTML8)    PDF(pc) (2633KB)(19)       Save

    Low-dose CT has the advantages of low radiation and high efficiency, but the noise and artifacts with low-dose CT images reduce the reliability of diagnosis. In order to improve the quality of low-dose CT images, this paper attempts to enhance the visuals of reconstructed CT images in the wavelet domain, and improve the running speed by combining the multi-dilated convolution and subpixel, so that the model can be better deployed to the CT equipment. The data set of "2016 AAPM Low Dose CT image Challenge" is used to evaluate the proposed method. Experimental results show that the visuals of reconstructed CT images are better. Compared with RED-CNN, the average PSNR of the proposed method is improved by 0.1428dB (1mm) / 0.0939dB (3mm), and the running speed on the CPU and GPU is increased by more than 55% and 50%, respectively.

    Table and Figures | Reference | Related Articles | Metrics