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Stability of Impulsive Neural Networks with Time‐Varying and Distributed Delays

Author

Listed:
  • Qi Luo
  • Xinjie Miao
  • Qian Wei
  • Zhengxin Zhou

Abstract

This work is devoted to investigating the stability of impulsive cellular neural networks with time‐varying and distributed delays. We use the new method of fixed point theory to obtain some new and concise sufficient conditions to ensure the existence and uniqueness of solution and the global exponential stability of trivial equilibrium. The presented algebraic criteria are easily checked and do not require the differentiability of delays.

Suggested Citation

  • Qi Luo & Xinjie Miao & Qian Wei & Zhengxin Zhou, 2013. "Stability of Impulsive Neural Networks with Time‐Varying and Distributed Delays," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).
    • Handle: RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:325310
    DOI: 10.1155/2013/325310
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    References listed on IDEAS

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    1. Wang, Xiaohu & Xu, Daoyi, 2009. "Global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 2713-2721.
    2. Zhang, Yutian & Luo, Qi, 2012. "Novel stability criteria for impulsive delayed reaction–diffusion Cohen–Grossberg neural networks via Hardy–Poincarè inequality," Chaos, Solitons & Fractals, Elsevier, vol. 45(8), pages 1033-1040.
    3. Li, Kelin & Zhang, Xinhua & Li, Zuoan, 2009. "Global exponential stability of impulsive cellular neural networks with time-varying and distributed delay," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1427-1434.
    4. Sakthivel, R. & Luo, J., 2009. "Asymptotic stability of nonlinear impulsive stochastic differential equations," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1219-1223, May.
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    Cited by:

    1. Jianmin Duan & Manfeng Hu & Yongqing Yang & Liuxiao Guo, 2013. "Stability Analysis of Stochastic Markovian Jump Neural Networks with Different Time Scales and Randomly Occurred Nonlinearities Based on Delay‐Partitioning Projection Approach," Abstract and Applied Analysis, John Wiley & Sons, vol. 2013(1).

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