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1.

図書

図書
Mark Girolami
出版情報: London : Springer, c1999  [ix], 271 p. ; 24 cm
シリーズ名: Perspectives in neural computing
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2.

図書

図書
edited by Erkki Oja and Samuel Kaski
出版情報: Amsterdam : Elsevier, 1999  ix, 390 p. ; 25 cm
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目次情報: 続きを見る
Selected papers only
Preface / Kohonen Maps
Analyzing and representing multidimentional quantitative and qualitative data: Demographic study of the / Rhône valley
The domeatic consumption of the Canadian families / M. Cottrell ; P. Gaubert ; P. Letremy ; P. Rousset
Value maps: Finding value in markets that are expensive / G.J. Deboeck
Data mining and knowledge discovery with emergent Self-Organizing Feature Maps for multivariate time series / A. Ultsch
Tree structured Self-Organizing Maps / P. Koikkalainen
On the optimization of Self-Organizing Maps by genetic algorithms / D. Polani
Self organization of a massive text document collection / T. Kohonen ; S. Kaski ; K. Lagus ; J. Salojárvi ; J. Honkela ; V. Paatero ; A. Saarela
Document classification with Self-Organizing Maps / D. Merkl
Navigation in databases using Self-Organizing Maps / S.A. Shumsky
Self-Organising Maps in computer aided design of electronic circuits / A. Hemani ; A. Postula
Modeling self-organization in the visual cortex / R. Miikkulainen ; J.A. Bednar ; Y. Choe ; J. Sirosh
A spatio-temporal memory based on SOMs with activity diffusion / N.R. Euliano ; J.C. Principe
Advances in modeling cortical maps / P.G. Morasso ; V. Sanguineti ; F. Frisone
Topology preservation in Self-Organizing Maps / T. Villmann
Second-order learing in Self-Organizing Maps / R. Der ; M. Herrmann
Energy functions for Self-Organizing Maps / T. Heskes
LVQ and single trial EEG classification / G. Pfurtscheller ; M. Pregenzer
Self-Organizing Map in categorization of voice qualities / L. Leinonen
Self-Organizing Map in analysis of large-scale industrial systems / O. Simula ; J. Ahola ; E. Alhoniemi ; J. Himberg ; J. Vesanto
Keyword index
Selected papers only
Preface / Kohonen Maps
Analyzing and representing multidimentional quantitative and qualitative data: Demographic study of the / Rhône valley
3.

図書

図書
International Conference on Artificial Neural Networks ; Institution of Electrical Engineers
出版情報: London : Institution of Electrical Engineers, 1999  2v.(xxix,1028p.) ; 30cm
シリーズ名: IEE conference publication
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4.

図書

図書
C. Lee Giles, Marco Gori, eds
出版情報: Berlin ; New York : Springer, c1998  xii, 434 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 1387 . Lecture notes in artificial intelligence
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5.

図書

図書
Frank C. Hoppensteadt, Eugene M. Izhikevich
出版情報: New York : Springer, c1997  xvi, 400 p. ; 25 cm
シリーズ名: Applied mathematical sciences ; v. 126
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6.

図書

図書
Witold Pedrycz
出版情報: Boca Raton, Fla. : CRC Press, c1998  284 p. ; 26 cm
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7.

図書

図書
edited by Omid Omidvar, Judith Dayhoff
出版情報: San Diego, Calif. : Academic Press, c1998  xvi, 351 p. ; 24 cm
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8.

図書

図書
Genevieve B. Orr, Klaus-Robert Müller (eds.)
出版情報: Berlin : Springer, c1998  vi, 432 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 1524
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目次情報: 続きを見る
Introduction
Speeding Learning
Preface
Efficient BackProp / Yann LeCun ; Leon Bottou ; Genevieve B. Orr ; Klaus-Robert Müller1:
Regularization Techniques to Improve Generalization
Early Stopping - But When? / Lutz Prechelt2:
A Simple Trick for Estimating the Weight Decay Parameter / Thorsteinn S. Rögnvaldsson3:
Controling the Hyperparameter Search in MacKay's Bayesian Neural Network Framework / Tony Plate4:
Adaptive Regularization in Neural Network Modeling / Jan Larsen ; Claus Svarer ; Lars Nonboe Andersen ; Lars Kai Han- sen5:
Large Ensemble Averaging / David Horn ; Ury Naftaly ; Nathan Intrator6:
Improving Network Models and Algorithmic Tricks
Square Unit Augmented, Radially Extended, Multilayer Perceptrons / Gary William Flake7:
A Dozen Tricks with Multitask Learning / Rich Caruana8:
Solving the Ill-Conditioning in Neural Network Learning / Patrick van der Smagt ; Gerd Hirzinger9:
Centering Neural Network Gradient Factors / Nicol N. Schraudolph10:
Avoiding Roundoff Error in Backpropagating Derivatives / 11:
Representing and Incorporating Prior Knowledge in Neural Network Training
Transformation Invariance in Pattern Recognition - Tangent Distance and Tangent Propagation / Patrice Y. Simard ; Yann A. LeCun ; John S. Denker ; Bernard Victorri12:
Combining Neural Networks and Context-Driven Search for On-Line, Printed Handwriting Recognition in the Newton / Larry S. Yaeger ; Brandyn J. Webb ; Richard F. Lyon13:
Neural Network Classification and Prior Class Probabilities / Steve Lawrence ; Ian Burns ; Andrew Back ; Ah Chung Tsoi ; C. Lee Gi- les14:
Applying Divide and Conquer to Large Scale Pattern Recognition Tasks / Jurgen Fritsch ; Michael Finke15:
Tricks for Time Series
Forecasting the Economy with Neural Nets: A Survey of Challenges and Solutions / John Moody16:
How to Train Neural Networks / Ralph Neuneier ; Hans Georg Zimmermann17:
Author Index
Subject Index
Introduction
Speeding Learning
Preface
9.

図書

図書
edited by Leon O. Chua ... [et al.]
出版情報: Boston : Kluwer Academic Publishers, c1998  103 p. ; 27 cm
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Guest Editorial / L. Chua ; E. Pierzchala ; G. Gulak ; A. Rodriguez-Vazquez
A 16 x 16 Cellular Neural Network Universal Chip: The First Complete Single-Chip Dynamic Computer Array with Distributed Memory and with Gray-Scale Input-Output / J. M. Cruz ; L. O. Chua
A 6 x 6 Cells Interconnection-Oriented Programmable Chip for CNN / M. Salerno ; F. Sargeni ; Vincenzo Bonaiuto
Analog VLSI Design Constraints of Programmable Cellular Neural Networks / P. Kinget ; M. Steyaert
Focal-Plane and Multiple Chip VLSI Approaches to CNNs / M. Anguita ; F. J. Pelayo ; E. Ros ; D. Palomar ; A. Prieto
Architecture and Design of 1-D Enhanced Cellular Neural Network Processors for Signal Detection / M. Y. Wang ; B. J. Sheu ; T. W. Berger ; W. C. Young ; A. K. Cho
Analog VLSI Circuits for Competitive Learning Networks / H. C. Card ; D. K. McNeill ; C. R. Schneider
Design of Neural Networks Based on Wave-Parallel Computing Technique / Y. Yuminaka ; Y. Sasaki ; T. Aoki ; T. Higuchi
Guest Editorial / L. Chua ; E. Pierzchala ; G. Gulak ; A. Rodriguez-Vazquez
A 16 x 16 Cellular Neural Network Universal Chip: The First Complete Single-Chip Dynamic Computer Array with Distributed Memory and with Gray-Scale Input-Output / J. M. Cruz ; L. O. Chua
A 6 x 6 Cells Interconnection-Oriented Programmable Chip for CNN / M. Salerno ; F. Sargeni ; Vincenzo Bonaiuto
10.

図書

図書
by Te-Won Lee
出版情報: Boston : Kluwer Academic Publishers, c1998  xxxiii, 210 p. ; 24 cm
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目次情報: 続きを見る
Abstract
Preface
Acknowledgments
List of Figures
List of Tables
Abbreviations and Symbols
Introduction
Independent Component Analysis: Theory / Part I:
Basics / 1:
Independent Component Analysis / 2:
A Unifying Information-Theoretic Framework for ICA / 3:
Blind Separation of Time-Delayed and Convolved Sources / 4:
ICA Using Overcomplete Representations / 5:
First Steps towards Nonlinear ICA / 6:
Independent Component Analysis: Applications / Part II:
Biomedical Applications of ICA / 7:
ICA for Feature Extraction / 8:
Unsupervised Classification with ICA Mixture Models / 9:
Conclusions and Future Research / 10:
Bibliography
About the Author
Index
Abstract
Preface
Acknowledgments
11.

図書

図書
edited by Lakhmi C. Jain, V. Rao Vemuri
出版情報: Boca Raton, Fla. : CRC Press, c1999  325 p. ; 25 cm
シリーズ名: The CRC Press international series on computational intelligence / series editor L. C. Jain
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12.

図書

図書
Pierre Baldi, Søren Brunak
出版情報: Cambridge, Mass. : The MIT Press, 1998  xviii, 351 p., [8] p. of plats ; 24 cm
シリーズ名: Adaptive computation and machine learning
Bradford book
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目次情報: 続きを見る
Series Foreword
Preface
Introduction / 1:
Biological Data in Digital Symbol Sequences / 1.1:
Genomes--Diversity, Size, and Structure / 1.2:
Proteins and Proteomes / 1.3:
On the Information Content of Biological Sequences / 1.4:
Prediction of Molecular Function and Structure / 1.5:
Machine Learning Foundations: The Probabilistic Framework / 2:
Introduction: Bayesian Modeling / 2.1:
The Cox-Jaynes Axioms / 2.2:
Bayesian Inference and Induction / 2.3:
Model Structures: Graphical Models and Other Tricks / 2.4:
Summary / 2.5:
Probabilistic Modeling and Inference: Examples / 3:
The Simplest Sequence Models / 3.1:
Statistical Mechanics / 3.2:
Machine Learning Algorithms / 4:
Dynamic Programming / 4.1:
Gradient Descent / 4.3:
EM/GEM Algorithms / 4.4:
Markov Chain Monte Carlo Methods / 4.5:
Simulated Annealing / 4.6:
Evolutionary and Genetic Algorithms / 4.7:
Learning Algorithms: Miscellaneous Aspects / 4.8:
Neural Networks: The Theory / 5:
Universal Approximation Properties / 5.1:
Priors and Likelihoods / 5.3:
Learning Algorithms: Backpropagation / 5.4:
Neural Networks: Applications / 6:
Sequence Encoding and Output Interpretation / 6.1:
Prediction of Protein Secondary Structure / 6.2:
Prediction of Signal Peptides and Their Cleavage Sites / 6.3:
Applications for DNA and RNA Nucleotide Sequences / 6.4:
Hidden Markov Models: The Theory / 7:
Prior Information and Initialization / 7.1:
Likelihood and Basic Algorithms / 7.3:
Learning Algorithms / 7.4:
Applications of HMMs: General Aspects / 7.5:
Hidden Markov Models: Applications / 8:
Protein Applications / 8.1:
DNA and RNA Applications / 8.2:
Conclusion: Advantages and Limitations of HMMs / 8.3:
Hybrid Systems: Hidden Markov Models and Neural Networks / 9:
Introduction to Hybrid Models / 9.1:
The Single-Model Case / 9.2:
The Multiple-Model Case / 9.3:
Simulation Results / 9.4:
Probabilistic Models of Evolution: Phylogenetic Trees / 9.5:
Introduction to Probabilistic Models of Evolution / 10.1:
Substitution Probabilities and Evolutionary Rates / 10.2:
Rates of Evolution / 10.3:
Data Likelihood / 10.4:
Optimal Trees and Learning / 10.5:
Parsimony / 10.6:
Extensions / 10.7:
Stochastic Grammars and Linguistics / 11:
Introduction to Formal Grammars / 11.1:
Formal Grammars and the Chomsky Hierarchy / 11.2:
Applications of Grammars to Biological Sequences / 11.3:
Likelihood / 11.4:
Applications of SCFGs / 11.6:
Experiments / 11.8:
Future Directions / 11.9:
Internet Resources and Public Databases / 12:
A Rapidly Changing Set of Resources / 12.1:
Databases over Databases and Tools / 12.2:
Databases over Databases / 12.3:
Databases / 12.4:
Sequence Similarity Searches / 12.5:
Alignment / 12.6:
Selected Prediction Servers / 12.7:
Molecular Biology Software Links / 12.8:
Ph.D. Courses over the Internet / 12.9:
HMM/NN Simulator / 12.10:
Statistics / A:
Decision Theory and Loss Functions / A.1:
Quadratic Loss Functions / A.2:
The Bias/Variance Trade-off / A.3:
Combining Estimators / A.4:
Error Bars / A.5:
Sufficient Statistics / A.6:
Exponential Family / A.7:
Gaussian Process Models / A.8:
Variational Methods / A.9:
Information Theory, Entropy, and Relative Entropy / B:
Entropy / B.1:
Relative Entropy / B.2:
Mutual Information / B.3:
Jensen's Inequality / B.4:
Maximum Entropy / B.5:
Minimum Relative Entropy / B.6:
Probabilistic Graphical Models / C:
Notation and Preliminaries / C.1:
The Undirected Case: Markov Random Fields / C.2:
The Directed Case: Bayesian Networks / C.3:
HMM Technicalities, Scaling, Periodic Architectures, State Functions, and Dirichlet Mixtures / D:
Scaling / D.1:
Periodic Architectures / D.2:
State Functions: Bendability / D.3:
Dirichlet Mixtures / D.4:
List of Main Symbols and Abbreviations / E:
References
Index
Series Foreword
Preface
Introduction / 1:
13.

図書

図書
edited by Cornelius T. Leondes
出版情報: San Diego : Academic Press, c1998  xxix, 460 p. ; 24 cm
シリーズ名: Neural network systems techniques and applications ; vol. 1
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14.

図書

図書
edited by Omid Omidvar, Patrick van der Smagt
出版情報: San Diego ; Tokyo : Academic Press, c1997  xvii, 346 p. ; 24 cm
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Neural Network Sonar as a Perceptual Modality for Robotics / W.T. Miller III ; A.L. Kun,lt;/i>
Dynamic Balance of a Biped Walking / Robot. P. van der Smagt ; F. Groen,lt;/i>
Visual Feedback in Motion / D. DeMers ; K. Kreutz-Delgado,lt;/i>
Inverse Kinematics of Dextrous Manipulators / Y. Jin, T. Pipe ; A. Winfield,lt;/i>
Stable Manipulator Trajectory Control Using Neural Networks / P. Gaudiano ; F.H. Guenther ; E. Zalama,lt;/i>
The Neural Dynamics Approach to Sensory-Motor Control / A. Buhlmeier ; G. Maneuffel,lt;/i>
Operant Conditioning in Robots / B. Hallam ; J. Hallam ; G. Hayes,lt;/i>
A Dynamic Net for Robot Control / Ben Krise ; J. van Dam,lt;/i>
Neural Vehicles / J. Heikkonen ; P. Koikkalainen,lt;/i>
Self-Organization and Autonomous Robots
Neural Network Sonar as a Perceptual Modality for Robotics / W.T. Miller III ; A.L. Kun,lt;/i>
Dynamic Balance of a Biped Walking / Robot. P. van der Smagt ; F. Groen,lt;/i>
Visual Feedback in Motion / D. DeMers ; K. Kreutz-Delgado,lt;/i>
15.

図書

図書
Martin Beckerman
出版情報: New York : Wiley, 1997  xviii, 427 p. ; 25 cm
シリーズ名: Adaptive and learning systems for signal processing, communications, and control
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16.

図書

図書
Jason Kingdon
出版情報: London : Springer, 1997  xii, 227 p. ; 24 cm
シリーズ名: Perspectives in neural computing
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17.

図書

図書
Carl G. Looney
出版情報: New York : Oxford University Press, 1997  xix, 458 p. ; 25 cm
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目次情報: 続きを見る
Preface
List of Tables
Fundamentals of Pattern Recognition / Part I:
Basic Concepts of Pattern Recognition / 0:
Decision-Theoretic Algorithms / 1:
Structural Pattern Recognition / 2:
Introductory Neural Networks / Part II:
Artificial Neural Network Structures / 3:
Supervised Training via Error Backpropagation: Derivations / 4:
Advanced Fundamentals of Neural Networks / Part III:
Acceleration and Stabilization of Supervised Gradient Training of MLPs / 5:
Supervised Training via Strategic Search / 6:
Advances in Network Algorithms for Classification and Recognition / 7:
Recurrent Neural Networks / 8:
Neural, Feature, and Data Engineering / Part IV:
Neural Engineering and Testing of FANNs / 9:
Feature and Data Engineering / 10:
Testing and Applications
Some Comparative Studies of Feedforward Artificial Neural Networks / 11:
Pattern Recognition Applications / 12:
Preface
List of Tables
Fundamentals of Pattern Recognition / Part I:
18.

図書

図書
James M. Bower and David Beeman
出版情報: Santa Clara, Calif. : TELOS, Springer-Verlag, c1995  xx, 409 p. ; 24 cm
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19.

図書

図書
Stig I. Andersson (ed.)
出版情報: Berlin ; New York : Springer-Verlag, c1995  vi, 260 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 888
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20.

図書

図書
Timothy Masters
出版情報: New York : J. Wiley, c1994  xiv, 417 p. ; 24 cm.
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目次情報: 続きを見る
The Role of Neural Networks in Signal and Image Processing
Neurons in the Complex Domain
Data Preparation for Neural Networks
Frequency-Domain Techniques
Time/Frequency Localization
Time/Frequency Applications
Image Processing in the Frequency Domain
Moment-Based Image Features
Tone/Texture Descriptors
Using the MLFN Program
Appendix
Bibliography
Index
The Role of Neural Networks in Signal and Image Processing
Neurons in the Complex Domain
Data Preparation for Neural Networks
21.

図書

図書
Teuvo Kohonen
出版情報: Berlin ; New York : Springer, c1995  ix, 362 p. ; 25 cm
シリーズ名: Springer series in information sciences ; 30
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目次情報: 続きを見る
Mathematical Preliminaries / 1:
Mathematical Concepts and Notations / 1.1:
Vector Space Concepts / 1.1.1:
Matrix Notations / 1.1.2:
Eigenvectors and Eigenvalues of Matrices / 1.1.3:
Further Properties of Matrices / 1.1.4:
On Matrix Differential Calculus / 1.1.5:
Distance Measures for Patterns / 1.2:
Measures of Similarity and Distance in Vector Spaces / 1.2.1:
Measures of Similarity and Distance Between Symbol Strings / 1.2.2:
Averages Over Nonvectorial Variables / 1.2.3:
Statistical Pattern Analysis / 1.3:
Basic Probabilistic Concepts / 1.3.1:
Projection Methods / 1.3.2:
Supervised Classification / 1.3.3:
Unsupervised Classification / 1.3.4:
The Subspace Methods of Classification / 1.4:
The Basic Subspace Method / 1.4.1:
Adaptation of a Model Subspace to Input Subspace / 1.4.2:
The Learning Subspace Method (LSM) / 1.4.3:
Vector Quantization / 1.5:
Definitions / 1.5.1:
Derivation of the VQ Algorithm / 1.5.2:
Point Density in VQ / 1.5.3:
Dynamically Expanding Context / 1.6:
Setting Up the Problem / 1.6.1:
Automatic Determination of Context-Independent Productions / 1.6.2:
Conflict Bit / 1.6.3:
Construction of Memory for the Context-Dependent Productions / 1.6.4:
The Algorithm for the Correction of New Strings / 1.6.5:
Estimation Procedure for Unsuccessful Searches / 1.6.6:
Practical Experiments / 1.6.7:
Neural Modeling / 2:
Models, Paradigms, and Methods / 2.1:
A History of Some Main Ideas in Neural Modeling / 2.2:
Issues on Artificial Intelligence / 2.3:
On the Complexity of Biological Nervous Systems / 2.4:
What the Brain Circuits Are Not / 2.5:
Relation Between Biological and Artificial Neural Networks / 2.6:
What Functions of the Brain Are Usually Modeled? / 2.7:
When Do We Have to Use Neural Computing? / 2.8:
Transformation, Relaxation, and Decoder / 2.9:
Categories of ANNs / 2.10:
A Simple Nonlinear Dynamic Model of the Neuron / 2.11:
Three Phases of Development of Neural Models / 2.12:
Learning Laws / 2.13:
Hebb's Law / 2.13.1:
The Riccati-Type Learning Law / 2.13.2:
The PCA-Type Learning Law / 2.13.3:
Some Really Hard Problems / 2.14:
Brain Maps / 2.15:
The Basic SOM / 3:
A Qualitative Introduction to the SOM / 3.1:
The Original Incremental SOM Algorithm / 3.2:
The "Dot-Product SOM" / 3.3:
Other Preliminary Demonstrations of Topology-Preserving Mappings / 3.4:
Ordering of Reference Vectors in the Input Space / 3.4.1:
Demonstrations of Ordering of Responses in the Output Space / 3.4.2:
Basic Mathematical Approaches to Self-Organization / 3.5:
One-Dimensional Case / 3.5.1:
Constructive Proof of Ordering of Another One-Dimensional SOM / 3.5.2:
The Batch Map / 3.6:
Initialization of the SOM Algorithms / 3.7:
On the "Optimal" Learning-Rate Factor / 3.8:
Effect of the Form of the Neighborhood Function / 3.9:
Does the SOM Algorithm Ensue from a Distortion Measure? / 3.10:
An Attempt to Optimize the SOM / 3.11:
Point Density of the Model Vectors / 3.12:
Earlier Studies / 3.12.1:
Numerical Check of Point Densities in a Finite One-Dimensional SOM / 3.12.2:
Practical Advice for the Construction of Good Maps / 3.13:
Examples of Data Analyses Implemented by the SOM / 3.14:
Attribute Maps with Full Data Matrix / 3.14.1:
Case Example of Attribute Maps Based on Incomplete Data Matrices (Missing Data): "Poverty Map" / 3.14.2:
Using Gray Levels to Indicate Clusters in the SOM / 3.15:
Interpretation of the SOM Mapping / 3.16:
"Local Principal Components" / 3.16.1:
Contribution of a Variable to Cluster Structures / 3.16.2:
Speedup of SOM Computation / 3.17:
Shortcut Winner Search / 3.17.1:
Increasing the Number of Units in the SOM / 3.17.2:
Smoothing / 3.17.3:
Combination of Smoothing, Lattice Growing, and SOM Algorithm / 3.17.4:
Physiological Interpretation of SOM / 4:
Conditions for Abstract Feature Maps in the Brain / 4.1:
Two Different Lateral Control Mechanisms / 4.2:
The WTA Function, Based on Lateral Activity Control / 4.2.1:
Lateral Control of Plasticity / 4.2.2:
Learning Equation / 4.3:
System Models of SOM and Their Simulations / 4.4:
Recapitulation of the Features of the Physiological SOM Model / 4.5:
Similarities Between the Brain Maps and Simulated Feature Maps / 4.6:
Magnification / 4.6.1:
Imperfect Maps / 4.6.2:
Overlapping Maps / 4.6.3:
Variants of SOM / 5:
Overview of Ideas to Modify the Basic SOM / 5.1:
Adaptive Tensorial Weights / 5.2:
Tree-Structured SOM in Searching / 5.3:
Different Definitions of the Neighborhood / 5.4:
Neighborhoods in the Signal Space / 5.5:
Dynamical Elements Added to the SOM / 5.6:
The SOM for Symbol Strings / 5.7:
Initialization of the SOM for Strings / 5.7.1:
The Batch Map for Strings / 5.7.2:
Tie-Break Rules / 5.7.3:
A Simple Example: The SOM of Phonemic Transcriptions / 5.7.4:
Operator Maps / 5.8:
Evolutionary-Learning SOM / 5.9:
Evolutionary-Learning Filters / 5.9.1:
Self-Organization According to a Fitness Function / 5.9.2:
Supervised SOM / 5.10:
The Adaptive-Subspace SOM (ASSOM) / 5.11:
The Problem of Invariant Features / 5.11.1:
Relation Between Invariant Features and Linear Subspaces / 5.11.2:
The ASSOM Algorithm / 5.11.3:
Derivation of the ASSOM Algorithm by Stochastic Approximation / 5.11.4:
ASSOM Experiments / 5.11.5:
Feedback-Controlled Adaptive-Subspace SOM (FASSOM) / 5.12:
Learning Vector Quantization / 6:
Optimal Decision / 6.1:
The LVQ1 / 6.2:
The Optimized-Learning-Rate LVQ1 (OLVQ1) / 6.3:
The Batch-LVQ1 / 6.4:
The Batch-LVQ1 for Symbol Strings / 6.5:
The LVQ2 (LVQ 2.1) / 6.6:
The LVQ3 / 6.7:
Differences Between LVQ1, LVQ2 and LVQ3 / 6.8:
General Considerations / 6.9:
The Hypermap-Type LVQ / 6.10:
The "LVQ-SOM" / 6.11:
Applications / 7:
Preprocessing of Optic Patterns / 7.1:
Blurring / 7.1.1:
Expansion in Terms of Global Features / 7.1.2:
Spectral Analysis / 7.1.3:
Expansion in Terms of Local Features (Wavelets) / 7.1.4:
Recapitulation of Features of Optic Patterns / 7.1.5:
Acoustic Preprocessing / 7.2:
Process and Machine Monitoring / 7.3:
Selection of Input Variables and Their Scaling / 7.3.1:
Analysis of Large Systems / 7.3.2:
Diagnosis of Speech Voicing / 7.4:
Transcription of Continuous Speech / 7.5:
Texture Analysis / 7.6:
Contextual Maps / 7.7:
Artifically Generated Clauses / 7.7.1:
Natural Text / 7.7.2:
Organization of Large Document Files / 7.8:
Statistical Models of Documents / 7.8.1:
Construction of Very Large WEBSOM Maps by the Projection Method / 7.8.2:
The WEBSOM of All Electronic Patent Abstracts / 7.8.3:
Robot-Arm Control / 7.9:
Simultaneous Learning of Input and Output Parameters / 7.9.1:
Another Simple Robot-Arm Control / 7.9.2:
Telecommunications / 7.10:
Adaptive Detector for Quantized Signals / 7.10.1:
Channel Equalization in the Adaptive QAM / 7.10.2:
Error-Tolerant Transmission of Images by a Pair of SOMs / 7.10.3:
The SOM as an Estimator / 7.11:
Symmetric (Autoassociative) Mapping / 7.11.1:
Asymmetric (Heteroassociative) Mapping / 7.11.2:
Software Tools for SOM / 8:
Necessary Requirements / 8.1:
Desirable Auxiliary Features / 8.2:
SOM Program Packages / 8.3:
SOM_PAK / 8.3.1:
SOM Toolbox / 8.3.2:
Nenet (Neural Networks Tool) / 8.3.3:
Viscovery SOMine / 8.3.4:
Examples of the Use of SOMLPAK / 8.4:
File Formats / 8.4.1:
Description of the Programs in SOM_PAK / 8.4.2:
A Typical Training Sequence / 8.4.3:
Neural-Networks Software with the SOM Option / 8.5:
Hardware for SOM / 9:
An Analog Classifier Circuit / 9.1:
Fast Digital Classifier Circuits / 9.2:
SIMD Implementation of SOM / 9.3:
Transputer Implementation of SOM / 9.4:
Systolic-Array Implementation of SOM / 9.5:
The COKOS Chip / 9.6:
The TInMANN Chip / 9.7:
NBISOM_25 Chip / 9.8:
An Overview of SOM Literature / 10:
Books and Review Articles / 10.1:
Early Works on Competitive Learning / 10.2:
Status of the Mathematical Analyses / 10.3:
Zero-Order Topology (Classical VQ) Results / 10.3.1:
Alternative Topological Mappings / 10.3.2:
Alternative Architectures / 10.3.3:
Functional Variants / 10.3.4:
Theory of the Basic SOM / 10.3.5:
The Learning Vector Quantization / 10.4:
Diverse Applications of SOM / 10.5:
Machine Vision and Image Analysis / 10.5.1:
Optical Character and Script Reading / 10.5.2:
Speech Analysis and Recognition / 10.5.3:
Acoustic and Musical Studies / 10.5.4:
Signal Processing and Radar Measurements / 10.5.5:
Industrial and Other Real-World Measurements / 10.5.6:
Process Control / 10.5.8:
Robotics / 10.5.9:
Electronic-Circuit Design / 10.5.10:
Physics / 10.5.11:
Chemistry / 10.5.12:
Biomedical Applications Without Image Processing / 10.5.13:
Neurophysiological Research / 10.5.14:
Data Processing and Analysis / 10.5.15:
Linguistic and AI Problems / 10.5.16:
Mathematical and Other Theoretical Problems / 10.5.17:
Applications of LVQ / 10.6:
Survey of SOM and LVQ Implementations / 10.7:
Glossary of "Neural" Terms / 11:
References
Index
Mathematical Preliminaries / 1:
Mathematical Concepts and Notations / 1.1:
Vector Space Concepts / 1.1.1:
22.

図書

図書
edited by A.B. Bulsari
出版情報: Amsterdam ; New York : Elsevier, 1995  ix, 680 p. ; 25 cm
シリーズ名: Computer-aided chemical engineering ; 6
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23.

図書

図書
L.P.J. Veelenturf
出版情報: London : Prentice Hall, 1995  xiv, 259 p. ; 25 cm
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24.

図書

図書
Yoshua Bengio
出版情報: London : International Thomson Computer Press, 1995  viii,167p. ; 24 cm
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25.

図書

図書
Abhijit S. Pandya, Robert B. Macy
出版情報: Boca Raton, Fla. : CRC Press, c1996  410 p. ; 25 cm.
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26.

図書

図書
edited by A.M.S. Zalzala and A.S. Morris
出版情報: New York ; Tokyo : Ellis Horwood, 1996  viii, 278 p. ; 25 cm
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27.

図書

図書
Gustavo Deco, Dragan Obradovic
出版情報: New York : Springer, c1996  xiii, 261 p. ; 25 cm
シリーズ名: Perspectives in neural computing
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28.

図書

図書
Kenneth Hunt, George Irwin and Kevin Warwick (eds.)
出版情報: Berlin ; New York : Springer, c1995  278 p. ; 24 cm
シリーズ名: Advances in industrial control
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29.

図書

図書
Sigeru Omatu, Marzuki Khalid and Rubiyah Yusof
出版情報: New York : Springer, c1996  xiii, 255 p. ; 24 cm
シリーズ名: Advances in industrial control
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30.

図書

図書
B.D. Ripley
出版情報: New York : Cambridge University Press, 1996  xi, 403 p. ; 26 cm
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目次情報: 続きを見る
Introduction and examples / 1:
Statistical decision theory / 2:
Linear discriminant analysis / 3:
Flexible discriminants / 4:
Feed-forward neural networks / 5:
Non-parametric methods / 6:
Tree-structured classifiers / 7:
Belief networks / 8:
Unsupervised methods / 9:
Finding good pattern features / 10:
statistical sidelines / Appendix:
Glossary
References
Author index
Subject index
Introduction and examples / 1:
Statistical decision theory / 2:
Linear discriminant analysis / 3:
31.

図書

図書
Takeshi Furuhashi, (ed.)
出版情報: Berlin ; New York ; Tokyo : Springer, c1995  viii, 223 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 1011 . Lecture notes in artificial intelligence
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32.

図書

図書
N. K. Bose, P. Liang
出版情報: New York ; Tokyo : McGraw-Hill, c1996  xxxiii, 478 p. ; 25 cm
シリーズ名: McGraw-Hill series in electrical and computer engineering ; . Communications and signal processing
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33.

図書

図書
Duc Truong Pham and Liu Xing
出版情報: London ; Tokyo : Springer-Verlag, c1995  xiv, 238 p. ; 24 cm
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34.

図書

図書
edited by Steven F. Zornetzer ... [et al.]
出版情報: San Diego : Academic Press, c1995  xxiv, 500 p. ; 24 cm
シリーズ名: Neural networks, foundations to applications
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35.

図書

図書
by Anne-Johan Annema
出版情報: Boston : Kluwer Academic Publishers, c1995  xiii, 238 p. ; 25 cm
シリーズ名: The Kluwer international series in engineering and computer science ; Analog circuits and signal processing
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36.

図書

図書
Suganda Jutamulia, editor
出版情報: Bellingham, Wash. : SPIE Optical Engineering Press, c1994  xviii, 692 p. ; 29 cm
シリーズ名: SPIE milestone series / Brian J. Thompson, general editor ; v. MS 96
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37.

図書

図書
Takeshi Furuhashi, Yoshiki Uchikawa, (eds.)
出版情報: Berlin : Springer-Verlag, c1996  viii, 243 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 1152 . Lecture notes in artificial intelligence
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38.

図書

図書
Hung T. Nguyen and Elbert A. Walker
出版情報: Boca Raton, Fla. ; Tokyo : CRC Press, c1997  266 p. ; 25 cm
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39.

図書

図書
M. Vidyasagar
出版情報: London : Springer, c1997  xviii, 383 p. ; 25 cm
シリーズ名: Communications and control engineering
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40.

図書

図書
P.J. Braspenning, F. Thuijsman, A.J.M.M. Weijters, (eds.)
出版情報: Berlin ; New York : Springer, c1995  vii, 293 p. ; 24 cm
シリーズ名: Lecture notes in computer science ; 931
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41.

図書

図書
Bart Kosko
出版情報: Englewood Cliffs, N.J. : Prentice Hall, c1992  xxvii, 449 p. ; 24 cm
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42.

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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43.

図書

図書
edited by Eric Goles and Servet Martínez
出版情報: Dordrecht ; Boston : Kluwer Academic Publishers, c1992  x, 207 p. ; 25 cm
シリーズ名: Mathematics and its applications ; v. 75
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44.

図書

図書
edited by R. Linggard, D.J. Myers and C. Nightingale
出版情報: London ; Tokyo : Chapman & Hall, c1992  xii, 442 p. ; 24 cm
シリーズ名: BT telecommunications series ; 1
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45.

図書

図書
edited by Gail A. Carpenter and Stephen Grossberg
出版情報: Cambridge, Mass. ; London : MIT Press, c1992  467 p. ; 26 cm
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46.

図書

図書
Tomas Hrycej
出版情報: New York, NY : Wiley, c1992  xiii, 235 p. ; 25 cm
シリーズ名: Sixth-generation computer technology series
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47.

図書

図書
N.B. Karayiannis, A.N. Venetsanopoulos
出版情報: Boston : Kluwer Academic, c1993  xii, 440 p. ; 25 cm
シリーズ名: The Kluwer international series in engineering and computer science ; SECS 209
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48.

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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49.

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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50.

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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