Global stability analysis of a nonlinear principal component analysis neural network

被引：0
|
作者：
MeyerBase, A
机构：
来源：
1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4 | 1997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 self-organization of a nonlinear, single-layer neural nei work is mathematically analyzed, in which a regular Hebbian rule and an anti-Hebbian rule are used for the adaptation of the connection weights between the constituent units. It is shown that the equilibrium points of this system are global asymptotically stable. Following some restrictive assumptions a nonlinear principal component analyzer can be constructed.
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页码：1785 / 1787
页数：3
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