The problem of stability analysis of static recurrent neural networks with interval time-varying delay is investigated in this paper. A new Lyapunov functional which contains some new double integral and triple integral terms are introduced. Information about the lower bound of the delay is fully used in the Lyapunov functional. Integral and double integral terms in the derivative of the Lyapunov functional are divided into some parts to get less conservative results. Some sufficient stability conditions are obtained in terms of linear matrix inequality (LMI). Numerical examples are given to illustrate the effectiveness of the proposed method.
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Stability analysis of static recurrent neural networks with interval time-varying delay
Semantic Scholar · Computer Science · 2013
Abstract
The problem of stability analysis of static recurrent neural networks with interval time-varying delay is investigated in this paper. A new Lyapunov functional which contains some new double integral and triple integral terms are introduced. Information about the lower bound of the delay is fully used in the Lyapunov functional. Integral and double integral terms in the derivative of the Lyapunov functional are divided into some parts to get less conservative results. Some sufficient stability conditions are obtained in terms of linear matrix inequality (LMI). Numerical examples are given to illustrate the effectiveness of the proposed method.