Global Exponential Stability of Antiperiodic Solutions for Discrete-Time Neural Networks with Mixed Delays and Impulses

Xiaofeng Chen and Qiankun Song

Discrete Dynamics in Nature and Society, 2012, vol. 2012, 1-23

Abstract:

The problem on global exponential stability of antiperiodic solution is investigated for a class of impulsive discrete-time neural networks with time-varying discrete delays and distributed delays. By constructing an appropriate Lyapunov-Krasovskii functional, and using the contraction mapping principle and the matrix inequality techniques, a new delay-dependent criterion for checking the existence, uniqueness, and global exponential stability of anti-periodic solution is derived in linear matrix inequalities (LMIs). Two simulation examples are given to show the effectiveness of the proposed result.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:168375

DOI: 10.1155/2012/168375

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