基于Lévy噪声的混合时滞中立型神经网络自适应同步研究
Year: 2020
Type: article
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.
Source: 应用数学和力学
Language: Chinese
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4251399396