Neural network implementations of independent component analysis

被引：0

作者：

Mutihac, R ^{[1
]}

Van Hulle, MM ^{[1
]}

机构：

[1] Catholic Univ Louvain, Lab Neuro Psychofysiol, B-3000 Louvain, Belgium

来源：

NEURAL NETWORKS FOR SIGNAL PROCESSING XII, PROCEEDINGS | 2002年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The performance of six neuromorphic adaptive structurally different algorithms was analyzed in blind separation of independent artificially generated signals using the stationary linear independent component analysis (ICA) model. The estimated independent components were assessed and compared aiming to rank the neural ICA implementations. All algorithms were run with different contrast functions, which were optimally selected on the basis of maximizing the sum of individual negentropies of the network outputs. Both subgaussian and supergaussian one-dimensional time series were employed throughout the numerical simulations.

引用

页码：505 / 514

页数：10

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