[1] Sun Changyin**, Fei Shumin, Feng Chunbo,. Absolute Exponential Stabilityof Generalized Dynamical Neural Networks* [J]. Journal of Southeast University (English Edition), 2002, 18 (2): 159-163. [doi:10.3969/j.issn.1003-7985.2002.02.012]

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Absolute Exponential Stabilityof Generalized Dynamical Neural Networks^*()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

18

Issue:

2002 2

Page:

159-163

Research Field:

Automation

Publishing date:

2002-06-30

Info

Title:

Absolute Exponential Stabilityof Generalized Dynamical Neural Networks^*

Author(s):

Sun Changyin^**;  Fei Shumin;  Feng Chunbo

Research Institute of Automation, Southeast University, Nanjing 210096, China

Keywords:

absolute exponential stability;  partial Lipschitz continuity;  neural networks

PACS:

TP183

DOI:

10.3969/j.issn.1003-7985.2002.02.012

Abstract:

This paper investigates the absolute exponential stability of generalized neural networks with a general class of partially Lipschitz continuous and monotone increasing activation functions. The main obtained result is that if the interconnection matrix T of the neural system satisfies that -T is an H-matrix with nonnegative diagonal elements, then the neural system is absolutely exponentially stable(AEST). The Hopfield network, Cellular neural network and Bidirectional associative memory network are special cases of the network model considered in this paper. So this work gives some improvements to the previous ones.

References:

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Memo

Memo:

* The project supported by the National Natural Science Foundation of China(69934010).
** Born in 1975, male, graduate.

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