Convergence Analysis of a Discrete-Time Single-Unit Gradient ICA Algorithm

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• 作者：Mao Ye ; Xue Li ; Chengfu Yang ; Zengan Gao
• 刊名：Lecture Notes in Computer Science
• 出版年：2006
• 出版时间：2006
• 年：2006
• 卷：3971
• 期：1
• 页码：pp.1140-1146
• 全文大小：297 KB

文摘

We revisit the one-unit gradient ICA algorithm derived from the kurtosis function. By carefully studying properties of the stationary points of the discrete-time one-unit gradient ICA algorithm, with suitable condition on the learning rate, convergence can be proved. The condition on the learning rate helps alleviate the guesswork that accompanies the problem of choosing suitable learning rate in practical computation. These results may be useful to extract independent source signals on-line.