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Advances in Neural Networks - ISNN 2005神经网络进展-ISNN 2005 第一部分

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Advances in Neural Networks - ISNN 2005神经网络进展-ISNN 2005 第一部分

最 低 价:¥1037.30

定 价:¥1152.60

作 者:Jun Wang 等著

出 版 社:北京燕山出版社

出版时间:2005-8-1

I S B N:9783540259121

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内容简介

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.

作者简介

目录

1 Theoretical Analysis
Population Coding, Bayesian Inference and Information Geometry
One-Bit-Matching ICA Theorem, Convex-Concave Programming, and Combinatorial Optimization
Dynamic Models for Intention (Goal-Directedness) Are Required by Truly Intelligent Robots
Differences and Commonalities Between Connectionism and Symbolicism
Pointwise Approximation for Neural Networks
On the Universal Approximation Theorem of Fuzzy Neural Networks with Random Membership Function Parameters
A Review: Relationship Between Response Properties of Visual Neurons and Advances in Nonlinear Approximation Theory
Image Representation in Visual Cortex and High Nonlinear Approximation
Generalization and Property Analysis of GENET
On Stochastic Neutral Neural Networks
Eigenanalysis of CMAC Neural Network
A New Definition of Sensitivity for RBFNN and Its Applications to Feature Reduction
Complexity of Error Hypersurfaces in Multilayer Perceptrons with General Multi-input and Multi-output Architecture
Nonlinear Dynamical Analysis on Coupled Modified Fitzhugh-Nagumo Neuron Model
Stability of Nonautonomous Recurrent Neural Networks with Time-Varying Delays
Global Exponential Stability of Non-autonomous Neural Networks with Variable Delay
A Generalized LMI-Based Approach to the Global Exponential Stability of Recurrent Neural Networks with Delay
A Further Result for Exponential Stability of Neural Networks with Time-Varying Delays
Improved Results for Exponential Stability of Neural Networks with Time-Varying Delays
Global Exponential Stability of Recurrent Neural Networks with Infinite Time-Varying Delays and Reaction-Diffusion Terms
Exponential Stability Analysis of Neural Networks with Multiple Time Delays
Exponential Stability of Cohen-Grossberg Neural Networks with Delays
Global Exponential Stability of Cohen-Grossberg Neural Networks with Time-Varying Delays and Continuously Distributed Delays
Exponential Stability of Stochastic Cohen-Grossberg Neural Networks with Time-Varying Delays
Exponential Stability of Fuzzy Cellular Neural Networks with Unbounded Delay
……
2 Model Design
3 Learning Methods
4 Optimization Methods
5 Kernel Methods
6 Component Analysis
Author Index

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