具有时滞的分数阶忆阻神经网络固定时间同步

doi:10.16180/j.cnki.issn1007-7820.2023.08.012

Abstract

Abstract:

The fixed-time synchronization problems are solved for fractional-order memristive neural networks. According to the voltage and current characteristics of memristors, the model of fractional-order memristive neural networks with time-varying delays is established. Different from the traditional calculation method of memristive synaptic weights based on the maximum absolute value, by introducing some transformations, using differential inclusion theory and set-valued maps, the fractional-order memristive neural networks are transformed into a type of fractional-order systems with uncertain parameters in the framework of Filippov solution. Based on the fixed-time stability theory and the theory of measurable selection, the sufficient conditions of fixed-time synchronization are given by constructing Lyapunov function and using inequality techniques, and the calculation formula of the upper bound for the synchronization time is given. By designing an appropriate state feedback controller, the master-slave systems can reach fixed-time synchronization, and the upper bound for the synchronization time is independent of the initial state for the systems. The simulation example shows that the designed controller makes the systems achieve synchronization quickly.

Key words: memristive neural networks, fractional-order calculus, time-varying delays, feedback control, fixed-time synchronization, Lyapunov stability theory, Filippov theory, differential inclusion, set-valued map

CLC Number:

TP13

WANG Kejie,TONG Dongbing. Fixed-Time Synchronization for Fractional-Order Memristive Neural Networks with Time-Delays[J].Electronic Science and Technology, 2023, 36(8): 81-87.

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References 19

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Fixed-Time Synchronization for Fractional-Order Memristive Neural Networks with Time-Delays

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