Adaptive Synchronization of Neutral Neural Networks With Mixed Delays and Lévy Noises
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摘要: 研究了带有Lévy噪声的混合时滞随机中立型神经网络的自适应同步问题.Lévy噪声的提出,使得网络里的噪声干扰由Gauss过程和Poisson点过程两部分组成,同时包含了连续的扰动和不连续的突触噪声.通过建立新的Lyapunov泛函,使用It?s公式以及不等式分析方法,得到误差系统的稳定性条件,给出了反馈控制器的更新率,从而进一步保证响应系统和驱动系统的自适应同步.最后,提供了一个数值实例,通过MATLAB相关仿真,说明前文所得结果的正确性.Abstract: The problem of feedback controllers designed to achieve adaptive synchronization was investigated for neutral neural networks with mixed delays and Lévy noises. The noise disturbance in the neural network model was driven by the Lévy stochastic process consisting of the Gaussian process and the Poisson point process, and involving continuous disturbances as well as discontinuous synaptic noises. Based on the Lyapunov functional, the It?s formula and the inequality analysis technique, the criteria to ensure adaptive stabilization for the error system were built. Moreover, the update rate of the feedback controller was given to enhance the adaptive synchronization of the response system and the drive system. Results of a simulation example show the effectiveness of the theoretical analysis.
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Key words:
- neutral neural network /
- Lévy noise /
- adaptive synchronization /
- mixed delays
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