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不确定时滞神经网络的自适应Q-S(滞后、预期和完全)时变同步及参数辨识

Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks.

作者信息

Yu Wenwu, Cao Jinde

机构信息

Department of Mathematics, Southeast University, Nanjing 210096, China.

出版信息

Chaos. 2006 Jun;16(2):023119. doi: 10.1063/1.2204747.

Abstract

In this paper, a new type of generalized Q-S (lag, anticipated, and complete) time-varying synchronization is defined. Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks have been considered, where the delays are multiple time-varying delays. A novel control method is given by using the Lyapunov functional method. With this new and effective method, parameters identification and Q-S (lag, anticipated, and complete) time-varying synchronization can be achieved simultaneously. Simulation results are given to justify the theoretical analysis in this paper.

摘要

本文定义了一种新型的广义Q-S(滞后、超前和完全)时变同步。研究了不确定时滞神经网络的自适应Q-S(滞后、超前和完全)时变同步及参数辨识问题,其中时滞为多个时变时滞。利用Lyapunov泛函方法给出了一种新颖的控制方法。通过这种新的有效方法,可以同时实现参数辨识和Q-S(滞后、超前和完全)时变同步。给出了仿真结果以验证本文的理论分析。

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