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This paper focuses on the stability problem of neutral-type recurrent neural networks with time-varying delay. Based on constructing a new augmented Lyapunov-Krasovskii functional (LKF) in which some of the symmetric matrices involved in LKF are not necessarily positive definite, an improved delay-dependent stability criterion is obtained in terms of linear matrix inequalities by applying reciprocally...
This paper is concerned with the problem of asymptotic stability of recurrent neural networks with time-varying delays. The activation functions are monotone nondecreasing with known lower and upper bounds, and satisfy a more general sector condition. A novel Lyapunov-Krasovsii functional based on delay-decomposition approach is constructed. By using Jensen inequality and reciprocally convex combination...
This paper studies the robust stability and passivity of delayed impulsive neural networks with polytopic type uncertainties and Markovian jumping parameters. Based on Lyapunov stability theory and a descriptor system approach, some sufficient conditions in form of linear matrix inequalities are derived. An illustrated numerical example is provided to demonstrate the effectiveness of the proposed...
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