Artificial Neural Networks人工神经网络

出版时间:2005-10  出版社:北京燕山出版社  作者:Dutch, W.; Duch, Wlodzislaw; Oja, Erkki  页数:1045  

内容概要

The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and Societies, LNCS has grown into the most comprehensive computer science research forum available.    The scope of LNCS, including its sub series LNAI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes  - Proceedings(published in time for the respective conference)   - Post-proceedings(consisting of thoroughly revised final full papers)   -research monographs(which may be based on outstanding PhD work, research projects, technical reports, etc.)、

书籍目录

New Neural Network Models Neuro-fuzzy Kolmogorov's Network A Neural Network Model for Inter-problem Adaptive Online Time Allocation Discriminant Parallel Perceptrons A Way to Aggregate Multilayer Neural Networks Generalized Net Models of MLNN Learning Algorithms Monotonic Multi-layer Perceptron Networks as Universal Approximators Short Term Memories and Forcing the Re-use of Knowledge for GenerMization Interpolation Mechanism of Functional NetworksSupervised Learning Algorithms Neural Network Topology Optimization Rough Sets-Based Recursive Learning Algorithm for Radial Basis Function Networks Support Vector Neural Training Evolutionary Algorithms for ReabTime Artificial Neural Network Training Developing Measurement Selection Strategy for Neural Network Models Nonlinear Regression with Piecewise Affine Models Based on RBFN Batch-Sequential Algorithm for Neural Networks Trained with Entropic Criteria Multiresponse Sparse Regression with Application to Multidimensional Scaling Training Neural Networks Using Taguchi Methods: Overcoming Interaction Problems A Global-Local Artificial Neural Network with Application to Wave Overtopping PredictionEnsemble-Based Learning Learning with Ensemble of Linear Perceptrons Combination Methods for Ensembles of RBFs Ensemble Techniques for Credibility Estimation of GAME Models ……Unsupervised LearningRecurrent neural NetworksReinforcement LearningBayesian Approaches to LearningLearning TheoryArtificial Neural Neworks for Syastem Modeling,Decision Making,Optimalizaation and ControlSpecial Session:Knowledge Extraction from Neural NetworksTemporal Data Analysis,Prediction and ForecastingSupport Vector Machines and Kerner-Based MethodsSoft Computing Methods for Data Representation,Analysis and ProcessingSpecial Session:Data Fusion for Industrial,Medical and Environmental Applications

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