Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
Recurrent Neural Networks for Prediction: Learning Algorithms,Architectures and Stability
Technical communique: Stability and robust stability for systems with a time-varying delay
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
A new method for stability analysis of recurrent neural networks with interval time-varying delay
IEEE Transactions on Neural Networks
Technical Communique: Delay-dependent criteria for robust stability of time-varying delay systems
Automatica (Journal of IFAC)
IEEE Transactions on Neural Networks
An improved global asymptotic stability criterion for delayed cellular neural networks
IEEE Transactions on Neural Networks
Stability Analysis for Neural Networks With Time-Varying Interval Delay
IEEE Transactions on Neural Networks
Delay-Dependent Stability for Recurrent Neural Networks With Time-Varying Delays
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
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This paper is concerned with the problem of stability analysis of recurrent neural networks with time-varying delay belonging to a given interval. By constructing a novel augmented Lyapunov functional which contains some triple-integral terms, improved delay-dependent stability criteria are derived in terms of linear matrix inequality (LMI) by introducing some free-weighting matrices and using integral inequality technique and convex combination method. Numerical examples are given to illustrate the effectiveness of the proposed method.