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Global convergence rate of recurrently connected neural networks.

作者信息

Chen Tianping, Lu Wenlian, Amari Shun-ichi

机构信息

Laboratory of Nonlinear Mathematics Science, Institute of Mathematics, Fudan University, Shanghai, China.

出版信息

Neural Comput. 2002 Dec;14(12):2947-57. doi: 10.1162/089976602760805359.

DOI:10.1162/089976602760805359
PMID:12487799
Abstract

We discuss recurrently connected neural networks, investigating their global exponential stability (GES). Some sufficient conditions for a class of recurrent neural networks belonging to GES are given. Sharp convergence rate is given too.

摘要

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