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.)

This publication is a part of a 3 quantity set that constitutes the refereed lawsuits of the 4th overseas 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 conscientiously reviewed and chosen from a complete of 1,975 submissions. The papers are geared up in topical sections on neural fuzzy keep an eye on, neural networks for keep an eye on purposes, adaptive dynamic programming and reinforcement studying, neural networks for nonlinear structures modeling, robotics, balance research of neural networks, studying and approximation, information mining and have extraction, chaos and synchronization, neural fuzzy platforms, education and studying algorithms for neural networks, neural community constructions, neural networks for trend reputation, SOMs, ICA/PCA, biomedical purposes, 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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Extra resources 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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PHysics Letters A, 353(2006) 318-325 4. : Synchronization Criteria of Lur’e Systems with Time-delay Feedback Control. Chaos Solitons & Fractals 23 (2005) 1285-1298 5. : Exponential Stability of Fuzzy Cellular Neural Networks with Distributed Delay. Physics Letters A 351 (2006)48-52 6. : Characterization of The Parameter-mismatching Effect on The Loss of Chaos Synchronization. Physical Review E 65 (2002), 026210 7. : Time-varying Synchronization of Chaotic Systems in The Presence of System Mismatch.

Chaos 16 (2004) 2923-2933 8. : Robust Synchronization of Delayed Neural Networks Based on Adaptive Control and Parameters Identification. Chaos, Solitons, Fractals 27 (2006) 905-913 9. : Chaotic Lag Synchronization of Coupled Delayed Neural Networks and Its Applications in Secure Communication. Circuits, Systems and Signal Processing 24 (2005) 599-613 10. : Global Synchronization of Impulsive Coupled Delayed Neural Networks. Wang, J and Yi, Z. ): Advances in Neural Networks ISNN 2006. Lecture Notes in Computer Science, Vol.

Global Synchronization in an Array of Delayed Neural Networks 2 35 Main Results In this section, Lyapunov functional method will be employed to investigate the global exponential synchronization of system (3). Theorem 1. Under the assumption (H), system (3) with initial condition (4) is globally exponentially synchronized, if there exist three positive definite matrices Pi > 0 (i = 1, 2, 3) and two positive diagonal matrices S, W such that the following LMIs are satisfied for all 1 ≤ i < j ≤ N : ⎡ −P1 C − CP1 + P3 LS + P1 A − N Gij P1 D ⎢ SL + AT P1 − N Gij DT P1 P2 − 2S Ωij =⎢ ⎣ 0 0 B T P1 0 ⎤ 0 P1 B ⎥ 0 0 ⎥ < 0, ⎦ −P3 LW W L −P2 − 2W (5) where L = diag(l1 , l2 , .

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