控制理论(社会学)
鉴定(生物学)
同步(交流)
人工神经网络
噪音(视频)
计算机科学
混乱的
简单(哲学)
混沌同步
自适应控制
差速器(机械装置)
人工智能
控制(管理)
频道(广播)
工程类
计算机网络
哲学
植物
认识论
图像(数学)
生物
航空航天工程
标识
DOI:10.1016/j.physa.2007.04.021
摘要
In this paper, an adaptive procedure to the problem of synchronization and parameters identification for chaotic neural networks with time-varying delay is introduced by combining the adaptive control and linear feedback with appropriate update law. Based on the invariance principle of functional differential equations, all the connection weight matrices can be efficiently estimated according to a simple, rigorous, and systematic technique. This approach is also able to track the changes in the operating parameters of the experimental neural networks rapidly. The speed of synchronization and parameters estimation can be adjusted under the adaptive gain properly chosen. In addition, the method is simple to implement in practice, and it is quite robust against the effect of slight noise in the given time series and the estimated value of a parameter fluctuates around the correct value.
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