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	Neural-based separating method for nonlinear mixtures
	Tan, Ying
	2007
关键词	BLIND SEPARATION SIGNAL SEPARATION ALGORITHM
英文摘要	A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the outputs of the separation system, is defined to extract the independent signals from their nonlinear mixtures. A learning algorithm for the parametric RBF network is established by using the stochastic gradient descent method. This approach is characterized by high learning convergence rate of weights, modular structure, as well as feasible hardware implementation. Successful experimental results are given at the end of this paper.; Computer Science, Artificial Intelligence; Computer Science, Theory & Methods; EI; CPCI-S(ISTP); 0
语种	英语
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/406452]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Tan, Ying. Neural-based separating method for nonlinear mixtures. 2007-01-01.

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