scholarly journals A Class of Frobenius Norm-Based Algorithms Using Penalty Term and Natural Gradient for Blind Signal Separation

2008 ◽  
Vol 16 (6) ◽  
pp. 1181-1193 ◽  
Author(s):  
U. Manmontri ◽  
P.A. Naylor
Keyword(s):  
Signal Separation ◽  
Blind Signal Separation ◽  
Frobenius Norm ◽  
Natural Gradient ◽  
Penalty Term ◽  
Blind Signal

Algorithm of Adaptive Online Blind Signal Separation Based on Matrix Separation

2013 ◽  
Vol 380-384 ◽  
pp. 3978-3981
Author(s):  
Dong Hui Xu ◽  
Hong Guang Ma ◽  
Wen Pu Guo ◽  
Dong Dong Yang
Keyword(s):  
Step Length ◽  
Signal Separation ◽  
Gradient Algorithm ◽  
Radar Signal ◽  
Blind Signal Separation ◽  
Natural Gradient ◽  
Separation Algorithm ◽  
Blind Signal ◽  
On Line ◽  
Adaptive Step

For the studied the over-determined blind source separation algorithm and its application in radar signal sorting. The reason that natural gradient algorithm of over-determined BSS can not stably converge eventually is analyzed. Aimed at the problem that the exiting methods are analyzed and researched. On-line BSS algorithm with adaptive step length based on separating matrix is presented to implement the optimum combination between the convergence speed and the steady-state error. At the same time, the algorithm can achieve a better separating result when the signal is randomly reduced or increased. The simulation result verifies the convergence stability and the separating effectivity of the two improved algorithms.

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