Fixed points and pth moment exponential stability of stochastic delayed recurrent neural networks with impulses

Guiling Chen; Onno Van Gaans; Sjoerd Verduyn Lunel

doi:10.1016/j.aml.2013.08.005

Fixed points and pth moment exponential stability of stochastic delayed recurrent neural networks with impulses

Guiling Chen^*, Onno Van Gaans, Sjoerd Verduyn Lunel

^*Corresponding author for this work

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

Abstract

New sufficient conditions for pth moment exponential stability of a class of impulsive stochastic delayed recurrent neural networks are presented by using fixed point theory. Our results neither require the boundedness monotonicity and differentiability of the activation functions nor differentiability of the time varying delays. A class of impulsive delayed neural networks without stochastic perturbations are also considered. An example is given to illustrate our main results.

Original language	English
Pages (from-to)	36-42
Number of pages	7
Journal	Applied Mathematics Letters
Volume	27
DOIs	https://doi.org/10.1016/j.aml.2013.08.005
Publication status	Published - Jan 2014

Keywords

Exponential stability
Fixed point theory
Impulses
Stochastic delayed neural networks
Variable delays

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10.1016/j.aml.2013.08.005

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title = "Fixed points and pth moment exponential stability of stochastic delayed recurrent neural networks with impulses",

abstract = "New sufficient conditions for pth moment exponential stability of a class of impulsive stochastic delayed recurrent neural networks are presented by using fixed point theory. Our results neither require the boundedness monotonicity and differentiability of the activation functions nor differentiability of the time varying delays. A class of impulsive delayed neural networks without stochastic perturbations are also considered. An example is given to illustrate our main results.",

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author = "Guiling Chen and Gaans, {Onno Van} and Lunel, {Sjoerd Verduyn}",

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AU - Gaans, Onno Van

AU - Lunel, Sjoerd Verduyn

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N2 - New sufficient conditions for pth moment exponential stability of a class of impulsive stochastic delayed recurrent neural networks are presented by using fixed point theory. Our results neither require the boundedness monotonicity and differentiability of the activation functions nor differentiability of the time varying delays. A class of impulsive delayed neural networks without stochastic perturbations are also considered. An example is given to illustrate our main results.

AB - New sufficient conditions for pth moment exponential stability of a class of impulsive stochastic delayed recurrent neural networks are presented by using fixed point theory. Our results neither require the boundedness monotonicity and differentiability of the activation functions nor differentiability of the time varying delays. A class of impulsive delayed neural networks without stochastic perturbations are also considered. An example is given to illustrate our main results.

KW - Exponential stability

KW - Fixed point theory

KW - Impulses

KW - Stochastic delayed neural networks

KW - Variable delays

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VL - 27

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JO - Applied Mathematics Letters

JF - Applied Mathematics Letters

ER -

Fixed points and pth moment exponential stability of stochastic delayed recurrent neural networks with impulses

Abstract

Keywords

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