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International Neural Network Conference

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Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 1 Large Scale Optoelectronic Integration of Asynchronous Analog Neural Networks
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    Chapter 2 A Hardware Emulator for Binary Neural Networks
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    Chapter 3 An Integrated Artificial Neuron Based on Junction-CCD Technology
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    Chapter 4 Fast Generation of Neuro-ASICs
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    Chapter 5 VLSI Architecture of the Boltzmann Machine Algorithm
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    Chapter 6 Systolic Synthesis of Neural Networks
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    Chapter 7 Smart: How to Simulate Huge Networks
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    Chapter 8 An Enhanced Parallel Planar Lattice Architecture for Large Scale Neural Network Simulations
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    Chapter 9 An Analog Chip Set for Multi-Layered Synchronous Boltzmann Machines
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    Chapter 10 DNNA: A Digital Neural Network Architecture
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    Chapter 11 The LNeuro-Chip: A Digital VLSI with on-Chip Learning Mechanism
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    Chapter 12 Implementation of a VLSI Feedback Neural Network Chip with Internal Automatic Identification of Successful Prototype Retrieval
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    Chapter 13 TFT Technology for Variable-Synapse Electronic Neural Networks
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    Chapter 14 Analog VLSI for Connectionist Learning
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    Chapter 15 Oscillatory States in Coupled Neural Oscillators
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    Chapter 16 The Minchinton Cell — Analog Input to the N-Tuple Net
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    Chapter 17 Digital Neurocomputer VLSI-Systems with Parallel Architecture
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    Chapter 18 A Systolic Implementation of the Self Organization Algorithm
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    Chapter 19 Digital Neurocomputers Oriented to a VLSI -Realization
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    Chapter 20 Network Analysis of an Optically Implemented Connectionist Architecture
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    Chapter 21 Optical Disk Based Processor for Handwritten Character Recognition
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    Chapter 22 Optical Implementation of Neural Networks with Fixed Global Interconnection and Local Adaptive Gain-Control
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    Chapter 23 Optical Neural Networks Using Electron Trapping Materials
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    Chapter 24 Learning experiment using erasable optically stimulable phosphor in optical neural network
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    Chapter 25 Operating Characteristics of a Second-Order Neural Network Classifier System
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    Chapter 26 Simulation of an Optoelectronically Implemented Neural Network for Early Visual Processing
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    Chapter 27 The Cognitive Challange for Neural Architectures
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    Chapter 28 Implementation of Back-Propagation on a VLSI Asynchronous Cellular Architecture
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    Chapter 29 VLSI Implementation of a Neural Associative Memory and its Application to Vector Quantization
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    Chapter 30 Implementing Semantic Networks in an Electronic Neural Network
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    Chapter 31 Kohonen Networks on Transputers: Implementation and Animation
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    Chapter 32 A Parallel Boltzmann Machine Simulator for Distributed Memory Multiprocessor Systems
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    Chapter 33 Optical Character Recognition and Neural-Net Chips
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    Chapter 34 Exploiting the Inherent Parallelism of Artificial Neural Networks to Achieve 1300 Million Interconnects per Second
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    Chapter 35 Bachus: A VLSI Architecture for a Large Binary Associative Memory
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    Chapter 36 A Reconfigurable Architecture for a VLSI Implementation of Artificial Neural Networks
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    Chapter 37 Multilayer Neural Networks on Distributed-Memory Multiprocessors
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    Chapter 38 Neural Network Simulation on the MasPar MP-1 Massively Parallel Processor
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    Chapter 39 Artificial Neural Network on a Massively Parallel Associative Architecture
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    Chapter 40 Using Xputers as Universal Accelerators for Neuro Network Simulation and its Applications
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    Chapter 41 NES: a Neuron-like net for a diagnostic Expert System
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    Chapter 42 Hardware Design Concepts for a Calm Neural Network Using 400 Simple Processors: System Architecture
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    Chapter 43 Transputer based simulation of a general purpose, fault tolerant neural network
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    Chapter 44 Resource-Allocation in a Fault Tolerant Neural Network
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    Chapter 45 A Data-Flow Linear Array Implementing Neural Network Architectures
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    Chapter 46 Self-Organizing Nonsymmetrical Algorithm and Nonlinear Synaptic Model of Neural Networks
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    Chapter 47 On Human Associative Ability (Associative Memory)
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    Chapter 48 The Static Reconfiguration of a Serial Superchip System Based on Neural Weights
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    Chapter 49 Parallel Implementation of the Kohonen Self-Organization Algorithm
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    Chapter 50 Architectures for Uncertain Reasoning
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    Chapter 51 Orthanc — an N-Tuple Network Development Enviroment
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    Chapter 52 A Virtual Machine Model for Artificial Neural Network Programming
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    Chapter 53 Optimisation of Network Structure using Genetic Techniques
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    Chapter 54 Neural Interactive Paradigm as a More Effective Computer System Environment
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    Chapter 55 Functional Descriptions of Neural Networks
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    Chapter 56 A Graphical Development Language for Integrated Knowledge Systems
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    Chapter 57 PYGMALION
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    Chapter 58 BRAINTRACER: A Software Package for the Simulation of Complex Neural Networks
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    Chapter 59 The MetaNet Network Environment for the Development of Modular Neural Networks
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    Chapter 60 An Actor Language for Connectionism based on Cellular Automata
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    Chapter 61 Architecture of the Neural Network Simulation Accelerator NEUROSIM/L
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    Chapter 62 Stability Study of Learning Vector Quantization
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    Chapter 63 An Experiment with 3-D Surface Maps to Illustrate Neural Network Performance
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    Chapter 64 On Backpropagation Learning of Edited Data Sets
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    Chapter 65 A Study of Learning and Generalization by Exhaustive Analysis
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    Chapter 66 Curvature-Driven Smoothing in Backpropagation Neural Networks
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    Chapter 67 Experimental Analysis of Performance of Temporal Supervised Learning Algorithm, Applied to a Long and Complex Sequence
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    Chapter 68 BFGS Optimization for Faster and Automated Supervised Learning
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    Chapter 69 Grow-and-Learn: An Incremental Method for Category Learning
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    Chapter 70 An Approach to Generalization Problem in Back-Propagation Learning
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    Chapter 71 A Training Algorithm for a Piecewise Linear Neural Network
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    Chapter 72 Supervised Learning Based on Kohonen’s Self-Organising Feature Maps
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    Chapter 73 Multi-Module Neural Networks for Classification
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    Chapter 74 Multi-Layer Versus Single-Layer Neural Networks and an Application to Reading Hand-Stamped Characters
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    Chapter 75 Delay-Insensitive Learning in a Feedforward Neural Network
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    Chapter 76 International Neural Network Conference
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    Chapter 77 A Fast Connectionist Learning Paradigm
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    Chapter 78 The Extraction of Rules from Multi-Layered Neural Networks
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    Chapter 79 Quantum Learning Algorithm for Multilayered Neural Network
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    Chapter 80 Training of a Neural Network with Topology Generation for the Classification Problem
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    Chapter 81 A Model of the Neural Network for Storage and Retrieval of Temporal Sequences
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    Chapter 82 Optimal Rule Induction in Neural Networks
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    Chapter 83 Learning by Asymmetric Parallel Boltzmann Machines
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    Chapter 84 Multi-Criteria Optimized Learning Rule for Optical Implementation
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    Chapter 85 Backpropagation Analogue Mapping Improved by Nonlinearities Modification
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    Chapter 86 Supervised Learning Using a Genetic Algorithm
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    Chapter 87 Structured Training for MLPs: Some Experiments on Netspeak with a Child’s Reading Scheme
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    Chapter 88 ALOPEX Algorithm for Supervised Learning in Layer Networks
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    Chapter 89 A Learning Rule in the Chebyshev Norm for Multilayer Perceptrons
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    Chapter 90 Symmetry and representability properties of feed-forward neural networks
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    Chapter 91 Hierarchical Architectures for Optimized Training
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    Chapter 92 Self-Organizing Neural Architectures for Vision, Learning, and Robotic Control
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    Chapter 93 Art 3: Self-Organization of Distributed Pattern Recognition Codes in Neural Network Hierarchies
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    Chapter 94 Application of Grossberg and Mingolla Neural Vision Model to Satellite Weather Imagery
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    Chapter 95 Representation of Uncertainty in Self-Organizing Neural Networks
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    Chapter 96 Improving the Learning Speed in Topological Maps of Patterns
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    Chapter 97 Reinforcement Learning with Interacting Continually Running Fully Recurrent Networks
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    Chapter 98 Hardware Realisable Learning Algorithms
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    Chapter 99 Supervised and Unsupervised Learning in Linear Networks
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    Chapter 100 Neural Models for Orthogonal and Oblique Factor Analyses: Towards dynamic data analysis of large sets of highly multidimensional objects
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    Chapter 101 A Learning Algorithm for Attribute Classes Construction
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    Chapter 102 Competitive Clustering
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    Chapter 103 Art: An Implementation of the New Direct Access Condition
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    Chapter 104 Elementary Operations in Neural Nets: Addition and Subtraction
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    Chapter 105 LEP — A Neural Model learning Reliably
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    Chapter 106 Pattern Recognition with a Multilayered Neural Network Trained with Dynamic Competitive Learning
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    Chapter 107 Weighted Hebbian Learning
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    Chapter 108 Self-Organizing Neural Network for Non-Parametric Regression Analysis
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    Chapter 109 A Drive Reinforcement Model for Visual Perception
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    Chapter 110 Bidirectional Associative Memory for Three Patterns
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    Chapter 111 Matrix Computations and Neural Associative Memories
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    Chapter 112 Partially Connected Models of Associative Memory
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    Chapter 113 Reinforcement Learning when Results are Delayed and Interleaved in Time
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    Chapter 114 Fault-tolerance in Iterative Learning Neural Networks
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    Chapter 115 Memory of Correlated Patterns by Associative Neural Networks with Improved Dynamics
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    Chapter 116 Hopfield Model of Neural Network with Unrestricted Self-Feedback
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    Chapter 117 A Structured Development for the Implementation of a Multilayer Neural Network (Cram Project)
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    Chapter 118 PROBAM Heteroassociative Multilayer Memory for Industrial Application
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    Chapter 119 Conditions on Activation Functions of Hidden Units for Learning by Backpropagation
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    Chapter 120 A Geometric Approach to the Structural Synthesis of Multilayer Perceptron Neural Networks
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    Chapter 121 A Rule-Based Approach to Neural Network Classifiers
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    Chapter 122 Choosing optimal network structure
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    Chapter 123 A Goal Seeking Neuron for Boolean Neural Networks
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    Chapter 124 A Spatial Approach to Feature Linking
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    Chapter 125 The Discrete Neuronal Model and the Probabilistic Discrete Neuronal Model
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    Chapter 126 Computing with Arrays of Coupled Oscillators
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    Chapter 127 Novelty Dependent Categorization and Learning in Calm Modules
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    Chapter 128 Equivalent TLU- and ∑П-Networks for Invariant Pattern Recognition
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    Chapter 129 The Concept of Learning Equilibrium Dynamics in the Development of Solid Networks
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    Chapter 130 FD-spectrums and their simulation by neural networks F — AI,connectionist,networks
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    Chapter 131 Rapid Learning of Pattern Sequences: A Novel Network Model
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    Chapter 132 Multi Class Pattern Association Using Digital N-Tuple Networks
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    Chapter 133 A Notion of Sequential Composition for Neural Nets
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    Chapter 134 Classifying Artificial Neural Network Architecture
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    Chapter 135 Most Neural Networks Compute in Steps
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    Chapter 136 A Macro Architecture for Dynamic Processing of Temporal Structures
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    Chapter 137 A Modular and Expandable Analog Integrated Neural Network
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    Chapter 138 Model of Hypothetical Visual Perceptive System
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    Chapter 139 Neural Network Unit Density: A Critical Biological Parameter
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    Chapter 140 Emergence of Complexity in the Dynamic of a Diluted Neural Network
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    Chapter 141 Informational Versus Bifurcative Use of Chaotic Dynamics in Neural Networks
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    Chapter 142 On Dynamics of Higher Order Neural Networks: Existences of Oscillations and Chaos
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    Chapter 143 Dynamical Change of Effective Degrees of Freedom in Fractal Chaos Model
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    Chapter 144 Temporal Patterns and Leaky Integrator Neurons
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    Chapter 145 An Analysis of the Delta Rule
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    Chapter 146 Classification capability of the two-layer perceptron
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    Chapter 147 Qualitative Analysis of Equilibrium Confinement and Exponential Stability of a Class of Dynamical Neural Networks
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    Chapter 148 A Global State Driven Cooling Schema for Simulated Annealing Used with Boltzmann Machine
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    Chapter 149 Independence from Temperature of Domains of Attraction in Neural Networks
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    Chapter 150 Self-Induced Noise in Neural Networks
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    Chapter 151 Some Remarks on Nonlinearities in Neural Networks
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    Chapter 152 On Pattern Recognition from the Edge-Images with a Nonlinear, Dynamical Network
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    Chapter 153 Linearly Independent Transformation by Hidden Units with Analytic Asymptotic Activation Function
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    Chapter 154 Reducing the Weight Space of a Net With Hidden Units to a Minimum Cone.
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    Chapter 155 The Kink Representation for Exclusive—OR
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    Chapter 156 Evaluation of the Functional Capacities of Multi-Layered Logical Neural Networks
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    Chapter 157 Theory of Information Propagation
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    Chapter 158 Monte-Carlo Learning: the LMS Rule and Random Weights can Form Non-Convex Decision Surfaces and Generalize
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    Chapter 159 Using Local Minima as Sequences Memories
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    Chapter 160 The Physical Correlates of Local Minima
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    Chapter 161 Dynamics and Associative Mapping in Additive Systems
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    Chapter 162 Learning Filter Systems
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    Chapter 163 Fokker-Planck Description of Learning in Backpropagation Networks
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    Chapter 164 Fundamental Structure/Behaviour Relationships in Synchronous Boolean Neural Networks
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    Chapter 165 Dynamics of Lateral Interaction Networks
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    Chapter 166 A Sparsely Connected Asymmetric Neural Network and Its Possible Application to the Processing of Transient Spatio-Temporal Signals
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    Chapter 167 Discrete Time Models of Noisy Networks.
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    Chapter 168 On the Computational Power of Neural Networks and Neural Automata
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    Chapter 169 Stable Neurodynamics and Symbolic Computation
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    Chapter 170 Eigenvalue Methods as a Tool for Global Analysis
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    Chapter 171 Coarticulation Invariance in Feedback Multilayer Perceptrons
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    Chapter 172 Analysis of Parallel and Sequential Boltzmann Machines
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    Chapter 173 Stochastic Dynamics and Input Dimensionality in a Two-Layer Neuronal Network for Modelling Multistable Perception
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    Chapter 174 The Effect of Non-Linear Synapses on Hierarchical Associative Memory
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    Chapter 175 A Structure for Neural Network Pattern Classifiers
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    Chapter 176 Convergence of the Vectors in Kohonen’s Learning Vector Quantization
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    Chapter 177 Recurrent Networks for Learning Stochastic Sequences
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    Chapter 178 Brain Building with GenNets
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    Chapter 179 Two Lower Bounds for Probabilistic Algorithms
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    Chapter 180 Thermal Comfort Sensor based on Probabilistic Energy Neural Network
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    Chapter 181 On the Back-Propagation Training of Neural Networks with Noisy Data
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    Chapter 182 Neural-Computing Within Esprit
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    Chapter 183 PYGMALION — Neurocomputing
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    Chapter 184 The Research Initiative in Pattern Recognition: A UK Collaborative Project in Neural Networks
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    Chapter 185 Galatea: A C-Library for Connectionist Applications
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    Chapter 186 An Overview of the First Year of ESPRIT Project ANNIE
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    Chapter 187 Neural Networks Activities at Thomson-CSF
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    Chapter 188 The British Telecom Connectionism Project
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    Chapter 189 The Impact of Neural Networks on the American Economy: 1990–2010
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    Chapter 190 Text-Dependent Speaker Identification Using Learning Vector Quantization
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Title
International Neural Network Conference
Published by
Springer Netherlands, January 1990
DOI 10.1007/978-94-009-0643-3
ISBNs
978-0-7923-0831-7, 978-9-40-090643-3
Authors

The International Neural Network Society (INNS), the IEEE Neural Network Council Cooperating Societies

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Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 67%
Student > Bachelor 1 33%
Readers by discipline Count As %
Economics, Econometrics and Finance 1 33%
Medicine and Dentistry 1 33%
Engineering 1 33%