Global Exponential Synchronization of Impulsive Chaotic Neural Networks
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摘要: 为研究脉冲神经网络的动力学行为,基于驱动-响应概念分析了两种具有可变时滞的脉冲混沌神经网络的全局指数同步性.假设激活函数满足严格单调递增,用神经网络的权系数、自反馈函数及激活函数构造不等式.根据向量Lyapunov函数理论,得到了驱动-响应系统全局指数同步充分条件的方程,即该方程小于0.数值仿真结果证明了该充分条件的正确性.Abstract: To study the dynamical behaviors of impulsive neural networks,the global exponential synchronization of a class of impulsive chaotic neural networks with time-varying delays was analyzed based on the conception of drive-response.On the assumption that the activation functions increased monotonously,inequalities were constructed using weighted coefficients,self-feedback functions and activation functions of the neural network.The equations of sufficient condition for global exponential synchronization of drive and response systems were obtained based on the theory of vector Lyapunov function,and all the equations were negative.The result of a numerical simulation demonstrated the correctness of the sufficient condition.
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Key words:
- neural network /
- impulse /
- time delays /
- synchronization
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