多比例时滞细胞神经网络的全局一致渐近稳定性

Global Uniform Asymptotic Stability of Cellular Neural Networks with Mutli-Porportional Delays

  • 摘要: 对一类具多比例时滞细胞神经网络进行研究, 利用变换zi(t)=yi(et) 将具多比例时滞细胞神经网络变换成变系数常时滞的细胞神经网络. 通过构造合适的Lyapunov泛函, 给出了几个保证该系统全局一致渐近稳定的时滞独立的充分条件, 并给出例子验证所得结论的正确性.

     

    Abstract: A class of cellular neural networks with multi-proportional delays is studied in this paper. The transformation zi(t)=yi(et) transforms cellular neural networks with multi-proportional delays into cellular neural networks with variable coefficient and constant delays, and then constructing Lyapunov functionals, some delay-independent sufficient conditions are given. These new sufficient conditions can ensure global uniform asymptotic stability of this system. An example is given to illustrate the correctness of obtained results.

     

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