Global robust exponential stability of interval neural networks with delays

Changyin Sun; Chun Bo Feng

doi:10.1023/A:1022999219879

Global robust exponential stability of interval neural networks with delays

Changyin Sun
, Chun Bo Feng

Southeast University, Nanjing

Research output: Contribution to journal › Article › peer-review

74 Scopus citations

Abstract

Global robust exponential stability of interval neural networks with delays was discussed. The delayed Hopfield network, bidirectional associative memory network and cellular neural network are special cases of the network model considered. Without assuming the boundedness, monotonicity and differentiability of the activation functions, the conditions ensuring the existence and uniqueness of the equilibrium were obtained.

Original language	English
Pages (from-to)	107-115
Number of pages	9
Journal	Neural Processing Letters
Volume	17
Issue number	1
DOIs	https://doi.org/10.1023/A:1022999219879
State	Published - Feb 2003
Externally published	Yes

Keywords

Activation function
Interval neural networks
Robust exponential stability

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10.1023/A:1022999219879

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title = "Global robust exponential stability of interval neural networks with delays",

abstract = "Global robust exponential stability of interval neural networks with delays was discussed. The delayed Hopfield network, bidirectional associative memory network and cellular neural network are special cases of the network model considered. Without assuming the boundedness, monotonicity and differentiability of the activation functions, the conditions ensuring the existence and uniqueness of the equilibrium were obtained.",

keywords = "Activation function, Interval neural networks, Robust exponential stability",

author = "Changyin Sun and Feng, \{Chun Bo\}",

year = "2003",

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doi = "10.1023/A:1022999219879",

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T1 - Global robust exponential stability of interval neural networks with delays

AU - Sun, Changyin

AU - Feng, Chun Bo

PY - 2003/2

Y1 - 2003/2

N2 - Global robust exponential stability of interval neural networks with delays was discussed. The delayed Hopfield network, bidirectional associative memory network and cellular neural network are special cases of the network model considered. Without assuming the boundedness, monotonicity and differentiability of the activation functions, the conditions ensuring the existence and uniqueness of the equilibrium were obtained.

AB - Global robust exponential stability of interval neural networks with delays was discussed. The delayed Hopfield network, bidirectional associative memory network and cellular neural network are special cases of the network model considered. Without assuming the boundedness, monotonicity and differentiability of the activation functions, the conditions ensuring the existence and uniqueness of the equilibrium were obtained.

KW - Activation function

KW - Interval neural networks

KW - Robust exponential stability

UR - https://www.scopus.com/pages/publications/0037314654

U2 - 10.1023/A:1022999219879

DO - 10.1023/A:1022999219879

M3 - 文章

AN - SCOPUS:0037314654

SN - 1370-4621

VL - 17

SP - 107

EP - 115

JO - Neural Processing Letters

JF - Neural Processing Letters

IS - 1

ER -

Global robust exponential stability of interval neural networks with delays

Abstract

Keywords

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