By Nan Jiang, Yixian Yang, Xiaomin Ma, Zhaozhi Zhang (auth.), Derong Liu, Shumin Fei, Zengguang Hou, Huaguang Zhang, Changyin Sun (eds.)
This ebook 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 rigorously reviewed and chosen from a complete of 1,975 submissions. The papers are geared up in topical sections on neural fuzzy keep watch over, neural networks for regulate purposes, 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 constructions, neural networks for development attractiveness, 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 functions of neural networks.
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 III PDF
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Additional resources for Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part III
Much method based on the BP neural networks is induced to approximate this complex nonlinear relationship. At the same time, two schemes of multiple models are proposed to improve the approximation performance of the BP neural network. Through the comparison among these schemes, it is shown that there is exact complex nonlinear relationship between the two diagnosis sheets. The works in the paper would be guidance for the diagnosis of the Apoplexy Syndromes and assistant for the further study of the relation between Western medicine and Traditional Chinese Medicine.
Fig. 6. ): Typical PD patterns of four defect types From the literature survey, several models and learning algorithms of ANN have been proposed for solving the patterns classification problems . In this paper, we establish a triple-layer feed-forward BPNN, as shown in Fig. 7, for solving the PD patterns classification problem. The number of neurons in the output layer is set at the number of defect types. The input data for the BPNN is the field measuring 3-D PD pattern. -H. -C. Chen pattern is pre-translated into a 1600x1 matrix.
But in the practicable program, those Filled-Function models with two or more parameters and exponential parameters are diﬃcult to be adjusted and often overﬂow. To avoid the drawbacks of existing Filled-Function models, a single-parameter Filled-Function model was presented and combined with QN method to optimize the weights and bias to minimize the error function. A new hybrid training algorithm is constructed for FFN. We also compare this new hybrid algorithm with QN method and discuss the merits and ﬂaws.
Advances in Neural Networks – ISNN 2007: 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, June 3-7, 2007, Proceedings, Part III by Nan Jiang, Yixian Yang, Xiaomin Ma, Zhaozhi Zhang (auth.), Derong Liu, Shumin Fei, Zengguang Hou, Huaguang Zhang, Changyin Sun (eds.)