Download Advances in Neural Networks – ISNN 2007: 4th International by Hongwei Wang, Hong Gu (auth.), Derong Liu, Shumin Fei, PDF

By Hongwei Wang, Hong Gu (auth.), Derong Liu, Shumin Fei, Zengguang Hou, Huaguang Zhang, Changyin Sun (eds.)

ISBN-10: 3540723927

ISBN-13: 9783540723929

ISBN-10: 3540723935

ISBN-13: 9783540723936

This publication is a part of a 3 quantity set that constitutes the refereed lawsuits of the 4th foreign Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007.

The 262 revised lengthy papers and 192 revised brief papers awarded have been rigorously reviewed and chosen from a complete of 1,975 submissions. The papers are equipped in topical sections on neural fuzzy regulate, neural networks for keep an eye on functions, adaptive dynamic programming and reinforcement studying, neural networks for nonlinear structures modeling, robotics, balance research of neural networks, studying and approximation, facts mining and have extraction, chaos and synchronization, neural fuzzy platforms, education and studying algorithms for neural networks, neural community constructions, neural networks for trend popularity, SOMs, ICA/PCA, biomedical functions, feedforward neural networks, recurrent neural networks, neural networks for optimization, aid vector machines, fault diagnosis/detection, communications and sign processing, image/video processing, and purposes of neural networks.

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Additional info for Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part II

Example text

Synchronization of coupled chaotic systems has been extensively investigated, for more information one may refer to [6-10, 12-13] and the references cited therein. However, in these papers, the coupling terms of the models been studied are always linear, to the best of our knowledge, up till now, there are very few results on an array of nonlinearly coupled neural networks. Based on the D. Liu et al. ): ISNN 2007, Part II, LNCS 4492, pp. 33–39, 2007. c Springer-Verlag Berlin Heidelberg 2007 34 J.

Throughout this paper, we define the synchronization state of the N 1 controlled coupled delayed neural network (2) as s(t) = xi (t), where N i=1 xi (t) (i = 1, 2 · · · , N ) are the solutions of the continuous coupled delayed neural network (1) [11]. For the later use, the definition with respect to robust impulsive synchronization of the controlled coupled delayed neural network (2) and the famous Halanay differential inequality on impulsive delay differential inequality are introduced as follows: Definition 1.

It is impossible to achieve complete synchronization. However, it is possible to make the synchronization error bounded by a small positive constant ε which is depended on the differences between parameters of two fuzzy neural networks. To the best of our knowledge, no report has been reported on quasisynchronization of two non-identical fuzzy neural networks. In this paper, we will investigate the effect of parameter mismatches on chaos synchronization of fuzzy neural networks by impulsive controls.

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Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part II by Hongwei Wang, Hong Gu (auth.), Derong Liu, Shumin Fei, Zengguang Hou, Huaguang Zhang, Changyin Sun (eds.)


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