Letters: Interval time-varying delay stability for neural networks

Authors:
Fernando de Oliveira Souza;Reinaldo Martinez Palhares
Affiliations:
Universidade Federal de São João del-Rei, Campus Alto Paraopeba, Rod. MG 443 Km 07, 36420-000 Ouro Branco, MG, Brazil;Universidade Federal de Minas Gerais, Departamento de Engenharia Eletrônica, Av. Antônio Carlos, 31270-010 Belo Horizonte, MG, Brazil
Venue:
Neurocomputing
Year:
2010

Citing 6
Cited 2

Stability of Time-Delay Systems

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Exponential stability of recurrent neural networks with both time-varying delays and general activation functions via LMI approach

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Delay-interval-dependent stability of recurrent neural networks with time-varying delay

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New LMT-based delay-dependent criterion for global asymptotic stability of cellular neural networks

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Stability Analysis for Neural Networks With Time-Varying Interval Delay

IEEE Transactions on Neural Networks
How delays affect neural dynamics and learning

IEEE Transactions on Neural Networks

Global robust passivity analysis for stochastic fuzzy interval neural networks with time-varying delays

Expert Systems with Applications: An International Journal
Global exponential stability of impulsive delayed reaction-diffusion neural networks via Hardy-Poincarè inequality

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Abstract

This paper presents a new linear matrix inequality (LMI) stability criterion for continuous-time artificial neural networks (ANN) with interval time-varying delay. The varying-time delay is taken as composition of a nominal positive value subject to a time-varying perturbation. The methodology is based on Gu's discretization technique and a strategy that decouples the system matrices from the Lyapunov functional matrices. Two numerical examples are performed to support the theoretical predictions.