Existence, uniqueness and global exponential stability of a periodic solution for a class of multidirectional associative memory neural network models

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成果类型：

期刊论文

作者：

Wang, Yi;Wang, Min;Zhou, Tiejun*

通讯作者：

Zhou, Tiejun

作者机构：

[Wang, Yi] Hunan Agr Univ, Coll Informat Sci & Technol, Changsha 410128, Hunan, Peoples R China.

[Wang, Min; Zhou, Tiejun] Hunan Agr Univ, Coll Sci, Changsha 410128, Hunan, Peoples R China.

通讯机构：

[Zhou, Tiejun] H

Hunan Agr Univ, Coll Sci, Changsha 410128, Hunan, Peoples R China.

语种：

英文

关键词：

Associative processing;Associative storage;Mapping;Associative memory;Associative memory neural networks;Distributed delays;Global exponential stability;Periodic coefficients;Periodic solution;Time varying networks

期刊：

Neural Computing and Applications

ISSN：

0941-0643

年：

2015

卷：

期：

页码：

979-986

DOI：

10.1007/s00521-014-1772-0

基金类别：

This work was supported by the Natural Science Foundation of Hunan Province (Grant No. 06JJ2100) and the Science Foundation of Hunan Agricultural University (Grant No. 07WD08). The authors are grateful for the constructive comments of the referees.

机构署名：

本校为第一且通讯机构

院系归属：

理学院

信息科学技术学院

摘要：

A multidirectional associative memory (MAM) neural network with periodic coefficients and distributed delays is studied. By constructing a Poincaré mapping, some sufficient conditions are obtained ensuring existence, uniqueness and the global exponential stability of a periodic solution of MAM neural network. The result is new to MAM neural networks. An example is given to illustrate the effectiveness of the result. ...

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Existence, uniqueness and global exponential stability of a periodic solution for a class of multidirectional associative memory neural network models

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