Stability analysis of delayed neural networks via a new integral inequality.

Yang, Bin; Wang, Juan; Wang, Jun · Neural Netw · 2017

basic_science · Level V

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Abstract

This paper focuses on stability analysis for neural networks systems with time-varying delays. A more general auxiliary function-based integral inequality is established and some improved delay-dependent stability conditions formulated in terms of linear matrix inequalities (LMIs) are derived by employing a suitable Lyapunov-Krasovskii functional (LKF) and the novel integral inequality. Three well-known application examples are provided to demonstrate the effectiveness and improvements of the proposed method.

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