Learning Convergence of CMAC Algorithm

被引：0
|
作者：
Chao He
Lixin Xu
Yuhe Zhang
机构：
[1] Beijing Institute of Technology,Department of Automatic Control
来源：
Neural Processing Letters | 2001年 / 14卷
关键词：
batch learning; CMAC; incremental learning; learning convergence; neural networks;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
CMAC convergence properties both in batch and in incremental learning are analyzed. The previous conclusions about the CMAC convergence, which are deduced under the condition that the articulation matrix is positive definite, are improved into the new less limited and more general conclusions in which no additive conditions are needed. An improved CMAC algorithm with self-optimizing learning rate is proposed from the new conclusions. Simulation results show the correctness of the new conclusions and the advantages of the improved algorithm.
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页码：61 / 74
页数：13
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