Advances in Neural Networks - ISNN 2005: Second International Symposium on Neural Networks, Chongqing, China, May 30 - June 1, 2005, Proceedings, Part 3
Jun Wang, Xiaofeng Liao, Zhang Yi
Springer, Aug 5, 2005 - Neural computers - 1077 pages
The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Networks, ISNN 2005, held in Chongqing, China in May/June 2005. The 483 revised papers presented were carefully reviewed and selected from 1.425 submissions. The papers are organized in topical sections on theoretical analysis, model design, learning methods, optimization methods, kernel methods, component analysis, pattern analysis, systems modeling, signal processing, image processing, financial analysis, control systems, robotic systems, telecommunication networks, incidence detection, fault diagnosis, power systems, biomedical applications, industrial applications, and other applications.
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A Novel Classifier with the ImmuneTraining Based Wavelet Neural Network
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adaptive control analysis application approach approximation Artificial Neural Networks basis function batch Berlin Heidelberg 2005 China classification closed-loop clustering Computer control scheme control system convergence data set defined denotes dynamics equation estimation fault diagnosis feature feedback filter Gaussian Heidelberg hidden layer IEEE IEEE Trans implemented initial intrusion detection ISNN iterations Kalman filter kernel learning algorithm Liao linear LNCS load forecasting LS-SVM Lyapunov Lyapunov function mapping matrix measurement mobile robot neural network based neuro-fuzzy neurons nodes noise nonlinear systems normal obtained on-line optimal output layer paper parameters performance PID controller plant predictive control problem proposed method RBF neural networks robust samples Section selected Self-Organizing Map sensor signal simulation results sliding mode sliding mode control Springer-Verlag Berlin Heidelberg stability structure Support Vector Machines technique tion torque tracking error traffic training data trajectory Tsinghua University update variables Wang wavelet weight Yi Eds