Adaptive exponential synchronization of chaotic recurrent neural networks with stochastic perturbation

机译：具有随机扰动的混沌递归神经网络的自适应指数同步

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This paper presents an adaptive exponential synchronization scheme for chaotic recurrent neural networks with stochastic perturbation. An adaptive synchronization controller is developed based on linear matrix inequality (LMI) and the controller can guarantee that the error of synchronization is exponentially ultimately bounded stable in the mean square. Moreover, we can make the bound of error as small as possible by appropriate selections of the controller parameters. Finally, an example is given to illustrate the validity of the proposed design.

机译：针对随机扰动的混沌递归神经网络，提出了一种自适应指数同步方案。基于线性矩阵不等式（LMI）开发了一种自适应同步控制器，该控制器可以保证同步误差在指数均方根下最终稳定。此外，通过适当选择控制器参数，我们可以使误差范围尽可能小。最后，给出一个例子来说明所提出设计的有效性。

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来源
《2012 IEEE International Conference on Automation and Logistics》|2012年|p.332- 336|共5页
会议地点 Zhengzhou(CN)
作者
Liu Leipo; Song Xiaona; Li Xiaoqiang;
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College of Electric and Information Engineering, Henan University of Science and Technology, Luoyang, China;

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原文格式 PDF
正文语种 eng
中图分类自动化系统;
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5. Learning in chaotic recurrent neural networks. [D] . Sussillo, David C. 2009

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8. Iterative prediction of chaotic time series using a recurrent neural network. Quarterly progress report, January 1, 1995--March 31, 1995 [R] . Bodruzzaman, M., Essawy, M. A. 1996

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Adaptive exponential synchronization of chaotic recurrent neural networks with stochastic perturbation

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