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1.

図書

図書
Bahram Nabet, Robert B. Pinter
出版情報: Boca Raton : CRC Press, c1991  xi, 182 p. ; 25 cm
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2.

図書

図書
Steven K. Rogers, Matthew Kabrisky ; contributing authors, Dennis W. Ruck and Gregory L. Tarr
出版情報: Bellingham, Wash., USA : SPIE Optical Engineering Press, c1991  xi, 220 p. ; 26 cm
シリーズ名: Tutorial texts in optical engineering ; v. TT 4
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3.

図書

図書
Paolo Antognetti and Veljko Milutinović, editors
出版情報: Englewood Cliffs, N.J. : Prentice Hall, 1991  4 v. ; 24 cm
シリーズ名: Prentice Hall advanced reference series ; . Engineering
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4.

図書

図書
by David P. Morgan, Christopher L. Scofield ; foreword by Leon N. Cooper
出版情報: Boston : Kluwer Academic Publishers, c1991  xvi, 391 p. ; 25 cm
シリーズ名: The Kluwer international series in engineering and computer science ; . VLSI, computer architecture, and digital signal processing
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5.

図書

図書
E. Domany, J.L. van Hemmen, K. Schulten, (eds.) ; [contributors, V. Braitenberg ... et al.]
出版情報: Berlin ; Tokyo : Springer-Verlag, c1991  xvi, 347 p. ; 25 cm
シリーズ名: Physics of neural networks
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6.

図書

図書
Hermann Haken
出版情報: Berlin ; Tokyo : Springer-Verlag, c1991  ix, 225 p. ; 25 cm
シリーズ名: Springer series in synergetics ; v. 50
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7.

図書

図書
Marilyn McCord Nelson and W.T. Illingworth
出版情報: Reading, Mass. : Addison-Wesley, c1991  xxii, 344 p. ; 25 cm
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8.

図書

図書
edited by Gail A. Carpenter and Stephen Grossberg
出版情報: Cambridge, Mass. : MIT Press, c1991  691 p. ; 26 cm
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目次情報: 続きを見る
List Of Authors
Editorial Preface
Neural Network Models for Pattern Recognition and Associative Memory / Chapter 1:
Preface
Abstract
Introduction / 1:
The McCulloch-Pitts Neuron / 2:
Adaptive Filter Formalism / 3:
Logical Calculus and Invariant Patterns / 4:
Perceptrons and Back-Coupled Error Correction / 5:
Adaline and Madaline / 6:
Multi-Level Perceptrons: Early Back Propagation / 7:
Later Back Propagation / 8:
Hebbian Learning / 9:
The Learning Matrix / 10:
Linear Associative Memory (LAM) / 11:
Real-Time Models and Embedding Fields / 12:
Instars and Outstars / 13:
Additive and Shunting Activation Equations / 14:
Learning Equations / 15:
Learning Space-Time Patterns: The Avalanche / 16:
Adaptive Coding and Category Formation / 17:
Shunting Competitive Networks / 18:
Competitive Learning / 19:
Computational Maps / 20:
Instability of Computational Maps / 21:
Adaptive Resonance Theory (ART) / 22:
ART for Associative Memory / 23:
Cognitron and Neocognitron / 24:
Simulated Annealing / 25:
Conclusion / 26:
Bibliography
References
Nonlinear Neural Networks: Principles, Mechanisms, and Architectures / Chapter 2:
Reference
Interdisciplinary Studies during the Nineteenth Century: Helmholtz, Maxwell, and Mach
The Schism between Physics and Psychology
The Nonlinear, Nonlocal, and Nonstationary Phenomena of Mind and Brain
Color Theory / A:
Top-Down Learning, Expectation, and Matching / B:
The Nature of an Enduring Synthesis
Sources of Neural Network Research: Binary, Linear, Continuous-Nonlinear
Binary
Linear
Continuous-Nonlinear / C:
Nonlinear Feedback between Fast Distributed STM Processing and Slow Associative LTM Processing
Principles, Mechanisms, and Architectures
Content-Addressable Memory Storage: A General STM Model and Liapunov Method
Other Liapunov Methods
Testing the Global Consistency of Decisions in Competitive Systems
Stable Production Strategies for a Competitive Market
Sensitive Variable-Load Parallel Processing by Shunting Cooperative-Competitive Networks: Automa...
Physiological Interpretation of Shunting Mechanisms as a Membrane Equation
Sigmoid Feedback, Contrast Enhancement, and Short Term Memory Storage by Shunting Feedback Netwo...
Competitive Learning Models
Stable Self-Organization of Pattern Recognition Codes
Internally Regulated Learning and Performance in Neural Models of Sensory-Motor Control: Adaptiv...
External Error Signals for Learning Adaptive Movement Gains: Push-Pull Opponent Processing
Match-Invariants: Internally Regulated Learning of an Invariant Self-Regulating Target Position ...
Presynaptic Competition for Long Term Memory: Self-Regulating Competitive Learning
Neural Pattern Discrimination / Chapter 3:
Connection with Learning Theory
Local Temporal Discrimination
Choices between Incompatible Behaviors: "Majority Rule" in Non-Recurrent "Interference Patterns"
Local Temporal Generalization: Variable Velocities of Motor Performance
Why are Sensory Pathways in Different Modalities Anatomically Different if Universal Discriminato...
Unselective Filtering of Spatial Patterns by Excitatory Networks
Two Stages of Non-Recurrent Inhibition for Pattern Discrimination
Specific versus Nonspecific Inhibitory Interneurons, Inhibition at the Axon Hillock, Presynaptic ...
Pattern Normalization in Type I Networks
High-Band Filters
Discrimination of Space-Time Patterns
Velocity and Orientation Detectors
Alternative Mechanisms of Pattern Normalization: Saturating Potentials in an On-Off Field, or Lo...
Proof of Proposition 1 / Appendix A:
Proof of Lemma 2 / Appendix B:
Proof of Theorem 1 / Appendix C:
Proof of Lemma 3 / Appendix D:
Proof of Proposition 3 / Appendix E:
Proof of Corollary 1 / Appendix F:
Proof of Proposition 4 / Appendix G:
Neural Expectation: Cerebellar and Retinal Analogs of Cells Fired by Learnable or Unlearned Pattern Classes / Chapter 4:
Neural Expectation: Cerebellar And Retinal Analogs of Cells Fired by Learnable or Unlearned Pattern ...
Theoretical Review
Retinal Analog of R Cells
A Learnable Preset Mechanism: Subtractive Case
Cerebellar Analogs of U Cells
A Learnable Present Mechanism: Multiplicative Case
Self-Organization of Orientation Sensitive Cells in the Striate Cortex / Chapter 5:
Self-Organization of Orientation Sensitive Cells In The Striate Cortex
The Model / I:
The Elements / a:
The Wiring of the Model / b:
The Afferent Organization / c:
The Learning Principle / d:
The Function of the Model / III:
Basic Equations of Evolution
Specification of Details
The Procedure of the Numerical Calculations
The Results without Learning
The Results after a Learning Phase / e:
The Effect of Non-Standard Stimuli
The Sensitivity to Nonspecific Input / g:
Redundancy of Information Storage / h:
Discussion / IV:
Structure of the Model and Generalizations
Comparison with Experiments
Adaptive Pattern Classification and Universal Recoding, I: Parallel Development and Coding of Neural Feature Detectors / Chapter 6:
Adaptive Pattern Classification And Universal Recoding, I: Parallel Development And Coding Of Neural...
The Tuning Process
Ritualistic Pattern Classification
Shunts versus Additive Interactions as Mechanisms of Pattern Classification
What Do Retinal Amacrine Cells Do?
Arousal as a Tuning Mechanism
Arousal as a Search Mechanism
Development of an STM Code
Appendix
The "Neural" Phonetic Typewriter by / Chapter 7:
The ''Neural" Phonetic Typewriter
Why is speech recognition difficult?
The promise of neural computers
Acoustic preprocessing
Vector quantization
The neural network
Shortcut learning algorithm
Phonotopic maps
Postprocessing in symbolic form
Hardware implementations and performance
Counterpropagation Networks / Chapter 8:
Counterpropagation Network
CPN Error Analysis
CPN Variants and Evolutes
Adaptive Pattern Classification and Universal Recoding, Ii: Feedback, Expectation, Olfaction, and Illusions / V:
Adaptive Pattern Classification And Universal Recoding, Ii: Feedback, Expectation, Olfaction, Illusi...
Adaptive Resonance: Stable Coding and Reset of STM
Adaptive Resonance in Reinforcement, Motivation, and Attention
Search and Lock Mechanism
Olfactory Coding and Learned Expectation
Modulation of Nonspecific Arousal by a Learned Expectation Mechanism
Universal Recoding
Search
Slow Noradrenergic Transmitter Accumulation-Depletion as a Search Mechanism
Spatial Frequency Adaptation
Afterimages
A Massively Parallel Architecture for A Self-Organizing Neural Pattern Recognition Machine / Chapter 10:
Introduction: Self-Organization of Neural Recognition Codes
Self-Scaling Computational Units, Self-Adjusting Memory Search, Direct Access, and Attentional Vi...
Bottom-Up Adaptive Filtering and Contrast-Enhancement in Short Term Memory
Top-Down Template Matching and Stabilization of Code Learning
Interactions between Attentional and Orienting Subsystems: STM Reset and Search
Attentional Gain Control and Attentional Priming
Matching: The 2/3 Rule
Code Instability and Code Stability
Using Context to Distinguish Signal from Noise in Patterns of Variable Complexity
Vigilance Level Tunes Categorical Coarseness: Disconfirming Feedback
Rapid Classification of an Arbitrary Type Font
Network Equations: Interactions between Short Term Memory and Long Term Memory Patterns
Direct Access to Subset and Superset Patterns
Weber Law Rule and Associative Decay Rule for Bottom-Up LTM Traces
Template Learning Rule and Associative Decay Rule for Top-Down LTM Traces
Direct Access to Nodes Coding Perfectly Learned Patterns
Initial Strengths of LTM Traces
Summary of the Model
Order of Search and Stable Choices in Short-Term Memory
Stable Category Learning
Critical Feature Patterns and Prototypes
Direct Access after Learning Self-Stabilizes
Order of Search: Mathematical Analysis
Order of Search: Computer Simulations
Biasing the Network towards Uncommitted Nodes
Computer Simulation of Self-Scaling Computational Units: Weighing the Evidence
Concluding Remarks: Self-Stabilization and Unitization within Associative Networks / 27:
Variations on Adaptive Resonance / Chapter 11:
Background
Adaptive Thresholding
Learning with Iterative Short-Time Pattern Presentations
Continuous ARC Operation
Conclusions
ART 2: Self-Organization of Stable Category Recognition Codes for Analog Input Patterns / Chapter 12:
Art 2: Self-Organization of Stable Category Recognition Codes for Analog Input Patterns
Adaptive Resonance Architectures
ART 1: Binary Input Patterns
ART 2: Analog Input Patterns
ART 2 Design Principles
ART 2 STM Equations: F1
ART 2 STM Equations: F2
ART 2 LTM Equations
ART 2 Reset Equations: The Orienting Subsystem
The Match-Reset Tradeoff: Choice of Top-down Initial LTM Values
Learning Increases Mismatch Sensitivity and Confirms Category Choice
Choosing a New Category: Bottom-up LTM Initial Values
The Stability-Plasticity Tradeoff
Alternative ART 2 Architectures
Adaptive Bidirectional Associative Memories / Chapter 13:
Introduction: Storing Data Pairs in Associative Memory Matrices
Discrete Bidirectional Associative Memory (BAM) Stability
BAM Correlation Encoding
Continuous BAMs
Adaptive BAMs
ART 3: Hierarchical Search Using Chemical Transmitters in Self-Organizing Pattern Recognition Architectures / Chapter 14:
Art 3: Hierarchical Search Using Chemical Transmitters in Self-Organizing Pattern Recognition Archit...
Introduction: Distributed Search of ART Network Hierarchies
An ART Search Cycle
ART 2: Three-Layer Competitive Fields
ART Bidirectional Hierarchies and Homology of Fields
ART Cascade
Search in an ART Hierarchy
A New Role for Chemical Transmitters in ART Search
Equations for Transmitter Production, Release, and Inactivation
Alternative ART 3 Systems
Transmitter Release Rate
System Dynamics at Input Onset: An Approximately Linear Filter
System Dynamics after Intrafield Feedback: Amplification of Transmitter Release by Postsynaptic ...
System Dynamics during Reset: Inactivation of Bound Transmitter Channels
Parametric Robustness of the Search Process
Summary of System Dynamics during a Mismatch-Reset Cycle
Automatic STM Reset by Real-Time Input Sequences
Reinforcement Feedback
Notation for Hierarchies
Trade-Off between Weight Size and Pattern Match
ART 3 Simulations: Mismatch Reset and Input Reset of STM Choices
Search Time Invariance at Different Vigilance Values
Reinforcement Reset
Input Hysteresis Simulation
Distributed Code Simulation
Alternative ART 3 Model Simulation
Simulation Equations
Artmap: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-organizing Neural Network / Chapter 15:
Artmap: Supervised Real-Time Learning and Classification of Nonstatationary Data by a Self-Organizin...
The ARTMAP system
ARTMAP simulations: Distinguishing edible and poisonous mushrooms
ART modules ARTa and ARTb
The Map Field
Simulation Algorithms
Neuronal Activity as A Shaping factor in The Self Organization of Neuron Assemblies / Chapter 16:
Neuronal Activity As A Shaping Factor in The Self-Organization of Neuron Assemblies
A Teleological Argument
Evidence for a Central Control of Local Hebbian Modifications
The Gating Mechanism
Functional Implications of Developmental Plasticity
Probing Cognitive Processes Through The Structure of Event-Related Potentials: An Experimental and Theoretical Analysis / Chapter 17:
Probing Cognitive Processes Through The Structure of Event-Related Potentials During Learning: An Ex...
Attentional Subsystem and Orienting Subsystem
STM Reset and Search
Matching via the 2/3 Rule
ERP Components
Experimental Paradigm
Experimental Results: ERP Profiles
Comparison of ERP Profiles with Adaptive Resonance Theory Mechanisms
Conclusion: The Relationship of Learning to ERPs
Unitization, Automaticity, Temploral Order, and Word Recongnition / Chapter 18:
Unitization, Automaticity, Temporal Order, and Word Recognition
The Word Length Effect
Unitization and Psychological Progress
The Temporal Chunking Problem
All Letters are Sublists
Expectancy Learning and Priming
The McClelland and Rumelhart Model
The Schneider and Shiffrin Model
Parallel Processing and Unlimited Capacity
The Functional Unit of Cognitive Processing: Not Spreading Activation
Capacity versus Matching
Adaptive Filter: The Processing Bridge between Sublist Masking and Temporal Order Information ov...
The LTM Invariance Principle: Temporal Order Information without a Serial Buffer
Spatial Frequency Analysis of Temporal Order Information
Speech Perception and Production by a Self-Organizing Neural Network / Chapter 19:
Speech Perception and Production By A Self-Organizing Neural Network
The Learning of Language Units
Low Stages of Processing: Circular Reactions and the Emerging Auditory and Motor Codes
The Vector Integration to Endpoint Model
Self-Stabilization of Imitation via Motor-to-Auditory Priming
Higher Stages of Processing: Context-Sensitive Chunking and Unitization of the Emerging Auditory ...
Masking Fields
Neural Dynamics of Adaptive Timing and Temporal Discrimination During Associative Learning / Chapter 20:
Introduction: Timing the Expected Delay of a Goal Object in a Spatially Distributed and Nonstatio...
Timing the Balance between Exploration for Novel Rewards and Consummation of Expected Rewards
Distinguishing Expected Nonoccurrences from Unexpected Nonoccurrences: Inhibiting the Negative Co...
Spectral Timing Model / Part I:
Spectral Timing Model: An Application of Gated Dipole Theory
Spectral Timing Equations
The Activation Spectrum
The Habituation Spectrum
The Gated Signal Spectrum
Temporally Selective Associative Learning / D:
The Doubly Gated Signal Spectrum / E:
The Output Signal / F:
Effect of Increasing ISI and US Intensity
Comparison with Nictitating Membrane Conditioning Data
Inverted U in Learning as a Function of ISI
Multiple Timing Peaks
Effect of Increasing US Duration
Effect of Increasing CS Intensity
Timed Gating of Read-Out From the Orienting Subsystem / Part II:
Locating the Timing Circuit within a Self-Organizing Sensory-Cogni-tive and Cognitive-Reinforcem...
Cognitive-Reinforcement Circuit
The Gated Dipole Opponent Process
Adaptive Timing as Spectral Conditioned Reinforcer Learning
Timed Inhibition of the Orienting Subsystem by Drive Representations
Timed Activation of the Hippocampus and the Contingent Negative Variation
Effect of CS Intensity on Timed Motor Behavior
Spatial Coding of Stimulus Intensity by a PTS Shift Map
Effect of Drugs on Timed Motor Behavior
Concluding Remarks: Timing Paradox and Multiple Types of Timing Circuits
Author Index
Subject Index
List Of Authors
Editorial Preface
Neural Network Models for Pattern Recognition and Associative Memory / Chapter 1:
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