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Robust Almost Periodic Dynamics for Interval Neural Networks with Mixed Time‐Varying Delays and Discontinuous Activation Functions

Author

Listed:
  • Huaiqin Wu
  • Sanbo Ding
  • Xueqing Guo
  • Lingling Wang
  • Luying Zhang

Abstract

The robust almost periodic dynamical behavior is investigated for interval neural networks with mixed time‐varying delays and discontinuous activation functions. Firstly, based on the definition of the solution in the sense of Filippov for differential equations with discontinuous right‐hand sides and the differential inclusions theory, the existence and asymptotically almost periodicity of the solution of interval network system are proved. Secondly, by constructing appropriate generalized Lyapunov functional and employing linear matrix inequality (LMI) techniques, a delay‐dependent criterion is achieved to guarantee the existence, uniqueness, and global robust exponential stability of almost periodic solution in terms of LMIs. Moreover, as special cases, the obtained results can be used to check the global robust exponential stability of a unique periodic solution/equilibrium for discontinuous interval neural networks with mixed time‐varying delays and periodic/constant external inputs. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.

Suggested Citation

  • Huaiqin Wu & Sanbo Ding & Xueqing Guo & Lingling Wang & Luying Zhang, 2013. "Robust Almost Periodic Dynamics for Interval Neural Networks with Mixed Time‐Varying Delays and Discontinuous Activation Functions," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:630623
    DOI: 10.1155/2013/630623
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    References listed on IDEAS

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    1. Yang, Xinsong & Huang, Chuangxia & Zhu, Quanxin, 2011. "Synchronization of switched neural networks with mixed delays via impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 44(10), pages 817-826.
    2. Wang, Jiafu & Huang, Lihong, 2012. "Almost periodicity for a class of delayed Cohen–Grossberg neural networks with discontinuous activations," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1157-1170.
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