Robust Stability in Interval Delayed Neural Networks of Neutral Type
In this paper, the problem of global robust stability (GRAS) is investigated for a class of interval neural networks described by nonlinear delayed differential equations of the neutral type. A sufficient criterion is derived by an approach combining the Lyapunov-Krasovskii functional with the linear matrix inequality (LMI). Finally, the effectiveness of the present results is demonstrated by a numerical example.
KeywordsLinear Matrix Inequality Robust Stability Recurrent Neural Network Cellular Neural Network Global Asymptotic Stability
Unable to display preview. Download preview PDF.