Table of Contents

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   Book Overview
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   Chapter 1 Dimensionality Reduction Based on ICA for Regression Problems
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   Chapter 2 A Functional Approach to Variable Selection in Spectrometric Problems
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   Chapter 3 The Bayes-Optimal Feature Extraction Procedure for Pattern Recognition Using Genetic Algorithm
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   Chapter 4 Speeding Up the Wrapper Feature Subset Selection in Regression by Mutual Information Relevance and Redundancy Analysis
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   Chapter 5 Effective Input Variable Selection for Function Approximation
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   Chapter 6 Comparative Investigation on Dimension Reduction and Regression in Three Layer Feed-Forward Neural Network
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   Chapter 7 On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition
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   Chapter 8 Learning Long Term Dependencies with Recurrent Neural Networks
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    Chapter 9 Adaptive On-Line Neural Network Retraining for Real Life Multimodal Emotion Recognition
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    Chapter 10 Time Window Width Influence on Dynamic BPTT(h) Learning Algorithm Performances: Experimental Study
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    Chapter 11 Framework for the Interactive Learning of Artificial Neural Networks
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    Chapter 12 Analytic Equivalence of Bayes a Posteriori Distributions
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    Chapter 13 Neural Network Architecture Selection: Size Depends on Function Complexity
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    Chapter 14 Competitive Repetition-suppression (CoRe) Learning
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    Chapter 15 Real-Time Construction of Neural Networks
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    Chapter 16 MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation
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    Chapter 17 A Variational Formulation for the Multilayer Perceptron
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    Chapter 18 Natural Conjugate Gradient Training of Multilayer Perceptrons
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    Chapter 19 Building Ensembles of Neural Networks with Class-Switching
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    Chapter 20 K-Separability
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    Chapter 21 Lazy Training of Radial Basis Neural Networks
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    Chapter 22 Investigation of Topographical Stability of the Concave and Convex Self-Organizing Map Variant
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    Chapter 23 Alternatives to Parameter Selection for Kernel Methods
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    Chapter 24 Faster Learning with Overlapping Neural Assemblies
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    Chapter 25 Improved Storage Capacity of Hebbian Learning Attractor Neural Network with Bump Formations
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    Chapter 26 Error Entropy Minimization for LSTM Training
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    Chapter 27 Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn  + +  Under Different Combination Rules
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    Chapter 28 Ensemble Learning with Local Diversity
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    Chapter 29 A Machine Learning Approach to Define Weights for Linear Combination of Forecasts
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    Chapter 30 A Game-Theoretic Approach to Weighted Majority Voting for Combining SVM Classifiers
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    Chapter 31 Improving the Expert Networks of a Modular Multi-Net System for Pattern Recognition
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    Chapter 32 Evaluating Users’ Satisfaction in Packet Networks Using Random Neural Networks
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    Chapter 33 Random Neural Networks for the Adaptive Control of Packet Networks
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    Chapter 34 Hardware Implementation of Random Neural Networks with Reinforcement Learning
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    Chapter 35 G-Networks and the Modeling of Adversarial Agents
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    Chapter 36 Development of a Neural Net-Based, Personalized Secure Communication Link
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    Chapter 37 Exact Solutions for Recursive Principal Components Analysis of Sequences and Trees
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    Chapter 38 Active Learning with the Probabilistic RBF Classifier
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    Chapter 39 Merging Echo State and Feedforward Neural Networks for Time Series Forecasting
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    Chapter 40 Language and Cognition Integration Through Modeling Field Theory: Category Formation for Symbol Grounding
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    Chapter 41 A Methodology for Estimating the Product Life Cycle Cost Using a Hybrid GA and ANN Model
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    Chapter 42 Using Self-Organizing Maps to Support Video Navigation
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    Chapter 43 Self-Organizing Neural Networks for Signal Recognition
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    Chapter 44 An Unsupervised Learning Rule for Class Discrimination in a Recurrent Neural Network
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    Chapter 45 On the Variants of the Self-Organizing Map That Are Based on Order Statistics
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    Chapter 46 On the Basis Updating Rule of Adaptive-Subspace Self-Organizing Map (ASSOM)
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    Chapter 47 Composite Algorithm for Adaptive Mesh Construction Based on Self-Organizing Maps
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    Chapter 48 A Parameter in the Learning Rule of SOM That Incorporates Activation Frequency
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    Chapter 49 Nonlinear Projection Using Geodesic Distances and the Neural Gas Network
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    Chapter 50 Contextual Learning in the Neurosolver
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    Chapter 51 A Computational Model for the Effect of Dopamine on Action Selection During Stroop Test
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    Chapter 52 A Neural Network Model of Metaphor Understanding with Dynamic Interaction Based on a Statistical Language Analysis
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    Chapter 53 Strong Systematicity in Sentence Processing by an Echo State Network
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    Chapter 54 Modeling Working Memory and Decision Making Using Generic Neural Microcircuits
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    Chapter 55 A Virtual Machine for Neural Computers
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    Chapter 56 Machine Cognition and the EC Cognitive Systems Projects: Now and in the Future
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    Chapter 57 A Complex Neural Network Model for Memory Functioning in Psychopathology
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    Chapter 58 Modelling Working Memory Through Attentional Mechanisms
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    Chapter 59 A Cognitive Model of Multi-objective Multi-concept Formation
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    Chapter 60 A Basis for Cognitive Machines
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    Chapter 61 Neural Model of Dopaminergic Control of Arm Movements in Parkinson’s Disease Bradykinesia
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    Chapter 62 Occlusion, Attention and Object Representations
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    Chapter 63 A Forward / Inverse Motor Controller for Cognitive Robotics
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    Chapter 64 A Computational Model for Multiple Goals
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    Chapter 65 Detection of a Dynamical System Attractor from Spike Train Analysis
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    Chapter 66 Recurrent Neural Networks Are Universal Approximators
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    Chapter 67 A Discrete Adaptive Stochastic Neural Model for Constrained Optimization
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    Chapter 68 Quantum Perceptron Network
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    Chapter 69 Critical Echo State Networks
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    Chapter 70 Rapid Correspondence Finding in Networks of Cortical Columns
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    Chapter 71 Adaptive Thresholds for Layered Neural Networks with Synaptic Noise
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    Chapter 72 Backbone Structure of Hairy Memory
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    Chapter 73 Dynamics of Citation Networks
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    Chapter 74 Processing of Information in Synchroneously Firing Chains in Networks of Neurons
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    Chapter 75 Phase Precession and Recession with STDP and Anti-STDP
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    Chapter 76 Visual Pathways for Detection of Landmark Points
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    Chapter 77 A Model of Grid Cells Based on a Path Integration Mechanism
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    Chapter 78 Temporal Processing in a Spiking Model of the Visual System
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    Chapter 79 Accelerating Event Based Simulation for Multi-synapse Spiking Neural Networks
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    Chapter 80 A Neurocomputational Model of an Imitation Deficit Following Brain Lesion
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    Chapter 81 Temporal Data Encoding and SequenceLearning with Spiking Neural Networks
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    Chapter 82 Optimal Tuning of Continual Online Exploration in Reinforcement Learning
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    Chapter 83 Vague Neural Network Controller and Its Applications
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    Chapter 84 Parallel Distributed Profit Sharing for PC Cluster
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    Chapter 85 Feature Extraction for Decision-Theoretic Planning in Partially Observable Environments
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    Chapter 86 Reinforcement Learning with Echo State Networks
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    Chapter 87 Reward Function and Initial Values: Better Choices for Accelerated Goal-Directed Reinforcement Learning
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    Chapter 88 Nearly Optimal Exploration-Exploitation Decision Thresholds
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    Chapter 89 Dual Adaptive ANN Controllers Based on Wiener Models for Controlling Stable Nonlinear Systems
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    Chapter 90 Online Stabilization of Chaotic Maps Via Support Vector Machines Based Generalized Predictive Control
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    Chapter 91 Morphological Neural Networks and Vision Based Mobile Robot Navigation
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    Chapter 92 Position Control Based on Static Neural Networks of Anthropomorphic Robotic Fingers
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    Chapter 93 Learning Multiple Models of Non-linear Dynamics for Control Under Varying Contexts
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    Chapter 94 A Study on Optimal Configuration for the Mobile Manipulator: Using Weight Value and Mobility
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    Chapter 95 VSC Perspective for Neurocontroller Tuning
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    Chapter 96 A Neural Network Module with Pretuning for Search and Reproduction of Input-Output Mapping
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    Chapter 97 Physical Mapping of Spiking Neural Networks Models on a Bio-inspired Scalable Architecture
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    Chapter 98 A Time Multiplexing Architecture for Inter-neuron Communications
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     Chapter 99 Neuronal Cell Death and Synaptic Pruning Driven by Spike-Timing Dependent Plasticity
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     Chapter 100 Effects of Analog-VLSI Hardware on the Performance of the LMS Algorithm
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     Chapter 101 A Portable Electronic Nose (E-Nose) System Based on PDA
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     Chapter 102 Optimal Synthesis of Boolean Functions by Threshold Functions
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     Chapter 103 Pareto-optimal Noise and Approximation Properties of RBF Networks