Online Algorithm of Blind Source Separation Based on Conjugate Gradient Method
Zhou Guo-biao · Journal of Nanchang University · 2007
Firstly what the Blind Signal Separation Problem(P1) in engineering is equivalent to an optimization problem(P2) is described,which is presented as the necessary and sufficient condition that makes the components of Y(t) statistically independent of each other.In the following investigation,we focus on searching methods of the optimization problem.As for the feature of the object function in(P2),the decision variable(separation matrix W) searched in traditional Euclidean space raise up with some difficulty computations and optimization methods are promote to running in curve Riemannian space to get optimal solution.On the basis of NGA and PDFA algorithms,combining the better performance of the score function estimation in online algorithm PDEA and faster convergence property of conjugate gradient method in solving BSS optimization problem,the Online Algorithm PEDA-CONJ is proposed,which has both virtues of adaptive learning and conjugate gradient convergence.The convergence rate of PEDA-CONJ is sped up,and there is a good performance in ill conditioned mixture when applying PEDA-CONJ in BSS.The convergence and efficiency of the algorithm are showed in the numerical simulations.