When is the least-mean fourth algorithm mean-square stable?

被引：0
|
作者：
Nascimento, VH [1 ]
Bermudez, JCM [1 ]
机构：
[1] Univ Sao Paulo, Dept Elect Syst Engn, Sao Paulo, SP, Brazil
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING | 2005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：
We show that the least-mean fourth and the least-mean mixed-norm algorithms are not mean-square stable when the input regressor is Gaussian-distributed. For the LMF algorithm, we propose an upper bound for the algorithm's probability of divergence, given the input and noise statistics, the step-size and the filter length. We show that the upper bound can also be used for the LMMN algorithm.
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页码：341 / 344
页数：4
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