Artificial Neural Networks人工神经网络

2005-10  

北京燕山出版社  

Dutch, W.; Duch, Wlodzislaw; Oja, Erkki  

1045  

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.）、

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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