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Finite-time \(\bf{{\it{L}}_2}\)-gain analysis for switched neural networks with time-varying delay

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Abstract

This paper considers the finite-time stability and finite-time boundedness problems for switched neural networks subject to \(L_2\)-gain disturbances. Sufficient conditions for the switched neural networks to be finite-time stable and finite-time bounded are derived. These conditions are delay-dependent and are given in terms of linear matrix inequalities. Average dwell time of switching signals is also given such that switched neural networks are finite-time stable or finite-time bounded. By resorting to the average dwell time approach and Lyapunov–Krasovskii functional technology, some new delay-dependent criteria guaranteeing finite-time boundedness and stabilizability with \(L_2\)-gain analysis performance are developed. An illustrative example is given to demonstrate the effectiveness of the proposed state estimator.

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Authors and Affiliations

  1. Department of Mathematics, Thiruvalluvar University, Vellore, 632 115, Tamilnadu, India

    M. Syed Ali & S. Saravanan

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  1. M. Syed Ali
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  2. S. Saravanan
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Correspondence to M. Syed Ali.

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Syed Ali, M., Saravanan, S. Finite-time \(\bf{{\it{L}}_2}\)-gain analysis for switched neural networks with time-varying delay. Neural Comput & Applic 29, 975–984 (2018). https://doi.org/10.1007/s00521-016-2498-y

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