Get Advances in Neural Networks – ISNN 2007: 4th International 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 ebook is a part of a 3 quantity set that constitutes the refereed complaints 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 offered have been rigorously reviewed and chosen from a complete of 1,975 submissions. The papers are prepared in topical sections on neural fuzzy regulate, neural networks for keep watch over functions, adaptive dynamic programming and reinforcement studying, neural networks for nonlinear platforms 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 buildings, neural networks for development attractiveness, SOMs, ICA/PCA, biomedical functions, feedforward neural networks, recurrent neural networks, neural networks for optimization, help vector machines, fault diagnosis/detection, communications and sign processing, image/video processing, and purposes of neural networks.

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Read or Download Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part II PDF

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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

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22. : The Global Stability of Fuzzy Cellular Neural Network. Circuits and Systems I: Fundamental Theory and Applications, 43(1996)880-883 23. : Impulsive Control Theory. Springer, Berlin, 2001. 24. : Impulsive Control, Complete and Lag Synchronization of Unified Chaotic System with Continuous Periodic Switch. Chaos Solitons & Fractals 26 (2005) 845-854 25. : Robust Synchronization of Delayed Neural Networks Based on Adaptive Control and Parameters Identification. com Abstract. In this paper, synchronization is investigated for an array of nonlinearly coupled identical connected neural networks with delay.

Lim e(t ) = 0 t →∞ where e = [e1 , e2 , e3 ]T Theorem: If the controllers are chosen as ⎧ u1 = −(25αˆ + 10)( y1 − x1 ) + y − k1e1 ⎪ ⎨ u2 = −(28 − 35αˆ ) x1 − (29αˆ − 1) y1 + x1 z1 + z − k2 e2 ⎪ u = − x y + 8 +αˆ z + ax ˆ + cz ˆ + by ˆ + x 2 − k3 e3 1 1 1 ⎩ 3 3 (10) And adaptive laws of parameters are chosen as ⎧ aˆ = − xe3 ⎪ ⎪bˆ = − ye3 ⎨ ⎪cˆ = − ze3 ⎪αˆ = 25( y − x )e − (35 x − 29 y )e − 1 z e 1 1 1 1 1 2 ⎩ 3 1 3 (11) Then system (8) globally synchronizes system (2) asymptotically. Where ki (i = 1, 2,3) are positive constants, aˆ , bˆ, cˆ, αˆ are estimates of a, b, c, α , respectively.

IEEE Trans. -I 40(11) (1993) 849-853 4. C. : Pattern Recognition Via Synchronization in Phase Locked Loop Neural Networks.

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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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