J4 ›› 2014, Vol. 41 ›› Issue (6): 1-5+88.doi: 10.3969/j.issn.1001-2400.2014.06.001

• Original Articles •     Next Articles

Improved laplace mixed model potential function algorithm for UBSS

FU Weihong;WANG Lu;MA Lifen   

  1.  (State Key Lab. of Integrated Service Networks, Xidian Univ., Xi'an  710071, China)
  • Received:2013-08-26 Online:2014-12-20 Published:2015-01-19
  • Contact: FU Weihong E-mail:whfu@mail.xidian.edu.cn

Abstract:

Aiming at the problem that the original Laplace Mixed Model Potential Function(LMMPF) algorithm  has high complexity and the random initial cluster center algorithm has a low accuracy and stability, we propose an improved LMMPF algorithm. Based on the concept of density, we can choose some high-density data as the initial cluster centers. These data obey the principle that the distance between the data in the same group is small and the distance between groups is great. Theoretical analysis and experimental results show that compared to the original LMMPF algorithm the complexity of the new algorithm becomes much lower while the estimated accuracy is reduced only a little bit. When the Signal to Noise Ration(SNR) is 10dB, the running time of the improved algorithm is reduced to 5%. Compared to the randomly-chosen algorithm, the new algorithm has a much higher accuracy: the accuracy rate of estimating the number of sources is raised from 61% to 85% and the mixing matrix estimated error is reduced from 0.47 to 0.27.

Key words: underdetemined blind source separation(UBSS), mixing matrix estimation, Laplace mixed model potential function(LMMPF), density, initial clustering centers

CLC Number: 

  • TN911.7