Stability analysis for neural networks with discontinuous neuron activations and impulses

Huaiqin Wu; Xiaoping Xue; Xiaozhu Zhong

Stability analysis for neural networks with discontinuous neuron activations and impulses

Huaiqin Wu^*
, Xiaoping Xue
, Xiaozhu Zhong

^*Corresponding author for this work

School of Mathematics

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

11 Scopus citations

Abstract

In this paper, by using the fixed point theorem of differential inclusion theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solution for neural networks with discontinuous neuron activations and impulses. The results show that the Forti's conjecture is true when neural networks are affected by impulses. Further, a numerical example is given to demonstrate the effectiveness of the results obtained in this paper.

Original language	English
Pages (from-to)	1537-1548
Number of pages	12
Journal	International Journal of Innovative Computing, Information and Control
Volume	3
Issue number	6 B
State	Published - Dec 2007

Keywords

Differential inclusions
Global exponential stability
Impulse
Neural networks

Cite this

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title = "Stability analysis for neural networks with discontinuous neuron activations and impulses",

abstract = "In this paper, by using the fixed point theorem of differential inclusion theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solution for neural networks with discontinuous neuron activations and impulses. The results show that the Forti's conjecture is true when neural networks are affected by impulses. Further, a numerical example is given to demonstrate the effectiveness of the results obtained in this paper.",

keywords = "Differential inclusions, Global exponential stability, Impulse, Neural networks",

author = "Huaiqin Wu and Xiaoping Xue and Xiaozhu Zhong",

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TY - JOUR

T1 - Stability analysis for neural networks with discontinuous neuron activations and impulses

AU - Wu, Huaiqin

AU - Xue, Xiaoping

AU - Zhong, Xiaozhu

PY - 2007/12

Y1 - 2007/12

N2 - In this paper, by using the fixed point theorem of differential inclusion theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solution for neural networks with discontinuous neuron activations and impulses. The results show that the Forti's conjecture is true when neural networks are affected by impulses. Further, a numerical example is given to demonstrate the effectiveness of the results obtained in this paper.

AB - In this paper, by using the fixed point theorem of differential inclusion theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solution for neural networks with discontinuous neuron activations and impulses. The results show that the Forti's conjecture is true when neural networks are affected by impulses. Further, a numerical example is given to demonstrate the effectiveness of the results obtained in this paper.

KW - Differential inclusions

KW - Global exponential stability

KW - Impulse

KW - Neural networks

UR - https://www.scopus.com/pages/publications/51049097071

M3 - 文章

AN - SCOPUS:51049097071

SN - 1349-4198

VL - 3

SP - 1537

EP - 1548

JO - International Journal of Innovative Computing, Information and Control

JF - International Journal of Innovative Computing, Information and Control

IS - 6 B

ER -

Stability analysis for neural networks with discontinuous neuron activations and impulses

Abstract

Keywords

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