Sufficient and Necessary Condition for Local Exponential Stabilityof Bidirectional ContinuousTime Associate Memory Neural Networks

Wang Lisheng; Tan Zheng; Zhang Zhijun

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Sufficient and Necessary Condition for Local Exponential Stabilityof Bidirectional ContinuousTime Associate Memory Neural Networks

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- Sufficient and Necessary Condition for Local Exponential Stabilityof Bidirectional ContinuousTime Associate Memory Neural Networks
- Acta Electronica Sinica Issue 7, (1999)
- 作者机构：
  
  西安交通大学电信学院信息工程研究所
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Published：1999
- 稿件说明：
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[1]王利生,谈正,张志军.连续双向联想记忆网络局部指数稳定的充要条件[J].电子学报,1999(07):120-122.

Wang Lisheng, Tan Zheng, Zhang Zhijun. Sufficient and Necessary Condition for Local Exponential Stabilityof Bidirectional ContinuousTime Associate Memory Neural Networks[J]. Acta Electronica Sinica, 1999, (7).
[1]王利生,谈正,张志军.连续双向联想记忆网络局部指数稳定的充要条件[J].电子学报,1999(07):120-122. DOI：

Wang Lisheng, Tan Zheng, Zhang Zhijun. Sufficient and Necessary Condition for Local Exponential Stabilityof Bidirectional ContinuousTime Associate Memory Neural Networks[J]. Acta Electronica Sinica, 1999, (7). DOI：

摘要

本文得到了连续双向联想记忆神经网络平衡点局部指数稳定的充要条件及平衡点指数吸引域的估计．所得结论对连续ＢＡＭ神经网络的设计及应用都很有意义．

Abstract

The sufficient and necessary condition for bidirectional continuoustime associate memory neural networks to be locally exponentially stable is obtained

and a characteristic function is defined for quantitatively study attractive domain of equilibrium point.

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