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

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  • Xiaofeng Chen
  • Qiankun Song

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.

Suggested Citation

  • Xiaofeng Chen & Qiankun Song, 2012. "Global Exponential Stability of Antiperiodic Solutions for Discrete-Time Neural Networks with Mixed Delays and Impulses," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-23, March.
    • Handle: RePEc:hin:jnddns:168375
    DOI: 10.1155/2012/168375
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