Neural networks
Subtitle: an introduction
By: B. Müller, J. Reinhardt, M.T. Strickland.
Contributors: Reinhardt, J. 1952-; Strickland, M. T. 1969-
Edition: 2nd updated and corr. ed.
Series: Physics of neural networks
Publisher: Springer-Verlag
Published: 1995
Place of publication: New York
Language: eng
Number of pages: 329
Subjects: Neural networks (Computer science)
Notes: Includes bibliographical references and index.

System requirements for disk: IBM PC or compatible; MS-DOS.
Table of contents: label: Part I
title: Models of Neural Networks; label: 1
title: The Structure of the Central Nervous System
pagenum: 3; label: 1.1
title: The Neuron
pagenum: 3; label: 1.2
title: The Cerebral Cortex
pagenum: 9; label: 2
title: Neural Networks Introduced
pagenum: 13; label: 2.1
title: A Definition
pagenum: 13; label: 2.2
title: A Brief History of Neural Network Models
pagenum: 13; label: 2.3
title: Why Neural Networks?
pagenum: 18; label: 2.3.1
title: Parallel Distributed Processing
pagenum: 18; label: 2.3.2
title: Understanding How the Brain Works
pagenum: 21; label: 2.3.3
title: General Literature on Neural Network Models
pagenum: 23; label: 3
title: Associative Memory
pagenum: 24; label: 3.1
title: Associative Information Storage and Recall
pagenum: 24; label: 3.2
title: Learning by Hebb's Rule
pagenum: 26; label: 3.3
title: Neurons and Spins
pagenum: 29; label: 3.3.1
title: The "Magnetic" Connection
pagenum: 29; label: 3.3.2
title: Parallel versus Sequential Dynamics
pagenum: 32; label: 3.4
title: Neural "Motion Pictures"
pagenum: 34; label: 4
title: Stochastic Neurons
pagenum: 38; label: 4.1
title: The Mean-Field Approximation
pagenum: 38; label: 4.2
title: Single Patterns
pagenum: 40; label: 4.3
title: Several Patterns
pagenum: 42; label: 5
title: Cybernetic Networks
pagenum: 46; label: 5.1
title: Layered Networks
pagenum: 46; label: 5.2
title: Simple Perceptrons
pagenum: 47; label: 5.2.1
title: The Perceptron Learning Rule
pagenum: 47; label: 5.2.2
title: "Gradient" Learning
pagenum: 48; label: 5.2.3
title: A Counterexample: The Exclusive-OR Gate
pagenum: 49; label: 6
title: Multilayered Perceptrons
pagenum: 52; label: 6.1
title: Solution of the XOR Problem
pagenum: 52; label: 6.2
title: Learning by Error Back-Propagation
pagenum: 53; label: 6.3
title: Boolean Functions
pagenum: 56; label: 6.4
title: Representation of Continuous Functions
pagenum: 60; label: 7
title: Applications
pagenum: 63; label: 7.1
title: Prediction of Time Series
pagenum: 63; label: 7.1.1
title: The Logistic Map
pagenum: 63; label: 7.1.2
title: A Nonlinear Delayed Differential Equation
pagenum: 64; label: 7.1.3
title: Nonlinear Prediction of Noisy Time Series
pagenum: 65; label: 7.2
title: Learning to Play Backgammon
pagenum: 67; label: 7.3
title: Prediction of the Secondary Structure of Proteins
pagenum: 69; label: 7.4
title: Net-Talk: Learning to Pronounce English Text
pagenum: 70; label: 8
title: More Applications of Neural Networks
pagenum: 72; label: 8.1
title: Neural Networks in High Energy Physics
pagenum: 74; label: 8.1.1
title: The Search for Heavy Quarks
pagenum: 74; label: 8.1.2
title: Triggering
pagenum: 78; label: 8.1.3
title: Mass Reconstruction
pagenum: 79; label: 8.1.4
title: The Jetnet Code
pagenum: 80; label: 8.2
title: Pattern Recognition
pagenum: 80; label: 8.2.1
title: Handwriting and Text Recognition
pagenum: 80; label: 8.2.2
title: Speech Recognition
pagenum: 83; label: 8.2.3
title: 3D Target Classification and Reconstruction
pagenum: 84; label: 8.3
title: Neural Networks in Biomedicine
pagenum: 85; label: 8.4
title: Neural Networks in Economics
pagenum: 87; label: 9
title: Network Architecture and Generalization
pagenum: 93; label: 9.1
title: Building the Network
pagenum: 93; label: 9.1.1
title: Dynamic Node Creation
pagenum: 93; label: 9.1.2
title: Learning by Adding Neurons
pagenum: 95; label: 9.2
title: Can Neural Networks Generalize?
pagenum: 96; label: 9.2.1
title: General Aspects
pagenum: 96; label: 9.2.2
title: Generalization and Information Theory
pagenum: 98; label: 9.3
title: Invariant Pattern Recognition
pagenum: 102; label: 9.3.1
title: Higher-Order Synapses
pagenum: 102; label: 9.3.2
title: Preprocessing the Input Patterns
pagenum: 105; label: 10
title: Associative Memory: Advanced Learning Strategies
pagenum: 108; label: 10.1
title: Storing Correlated Patterns
pagenum: 108; label: 10.1.1
title: The Projection Rule
pagenum: 109; label: 10.1.2
title: An Iterative Learning Scheme
pagenum: 111; label: 10.1.3
title: Repeated Hebbian Learning
pagenum: 114; label: 10.2
title: Special Learning Rules
pagenum: 117; label: 10.2.1
title: Forgetting Improves the Memory!
pagenum: 117; label: 10.2.2
title: Nonlinear Learning Rules
pagenum: 119; label: 10.2.3
title: Dilution of Synapses
pagenum: 122; label: 10.2.4
title: Networks with a Low Level of Activity
pagenum: 124; label: 11
title: Combinatorial Optimization
pagenum: 126; label: 11.1
title: NP-Complete Problems
pagenum: 126; label: 11.2
title: Optimization by Simulated Annealing
pagenum: 128; label: 11.3
title: Realization on a Network
pagenum: 130; label: 11.3.1
title: The Traveling-Salesman Problem
pagenum: 130; label: 11.3.2
title: Optical Image Processing
pagenum: 133; label: 12
title: VLSI and Neural Networks
pagenum: 135; label: 12.1
title: Hardware for Neural Networks
pagenum: 135; label: 12.2
title: Networks Composed of Analog Electronic Circuits
pagenum: 138; label: 13
title: Symmetrical Networks with Hidden Neurons
pagenum: 144; label: 13.1
title: The Boltzmann Machine
pagenum: 144; label: 13.2
title: The "Boltzmann" Learning Rule
pagenum: 145; label: 13.3
title: Applications
pagenum: 149; label: 14
title: Coupled Neural Networks
pagenum: 151; label: 14.1
title: Stationary States
pagenum: 151; label: 14.2
title: Recurrent Back-Propagation
pagenum: 153; label: 14.3
title: Back-Propagation Through Time
pagenum: 155; label: 14.4
title: Network Hierarchies
pagenum: 159; label: 15
title: Unsupervised Learning
pagenum: 162; label: 15.1
title: "Selfish" Neurons
pagenum: 162; label: 15.2
title: Learning by Competition
pagenum: 165; label: 15.2.1
title: "The Winner Takes All"
pagenum: 165; label: 15.2.2
title: Structure Formation by Local Inhibition
pagenum: 166; label: 15.2.3
title: The Kohonen Map
pagenum: 167; label: 15.3
title: Implementations of Competitive Learning
pagenum: 169; label: 15.3.1
title: A Feature-Sensitive Mapping Network
pagenum: 169; label: 15.3.2
title: The Neocognitron
pagenum: 174; label: 16
title: Evolutionary Algorithms for Learning
pagenum: 176; label: 16.1
title: Why Do Evolutionary Algorithms Work?
pagenum: 176; label: 16.2
title: Evolving Neural Networks
pagenum: 180; label: 16.2.1
title: Feed-Forward Networks
pagenum: 181; label: 16.2.2
title: Recurrent Networks
pagenum: 183; label: 16.3
title: Evolving Back-Propagation
pagenum: 185; label: Part II
title: Statistical Physics of Neural Networks; label: 17
title: Statistical Physics and Spin Glasses
pagenum: 191; label: 17.1
title: Elements of Statistical Mechanics
pagenum: 191; label: 17.2
title: Spin Glasses
pagenum: 194; label: 17.2.1
title: Averages and Ergodicity
pagenum: 194; label: 17.2.2
title: The Edwards-Anderson Model
pagenum: 196; label: 18
title: The Hopfield Network for p/N -> 0
pagenum: 201; label: 18.1
title: Evaluation of the Partition Function
pagenum: 201; label: 18.2
title: Equilibrium States of the Network
pagenum: 205; label: 19
title: The Hopfield Network for Finite p/N
pagenum: 209; label: 19.1
title: The Replica Trick
pagenum: 209; label: 19.1.1
title: Averaging over Patterns
pagenum: 211; label: 19.1.2
title: The Saddle-Point Approximation
pagenum: 215; label: 19.2
title: Phase Diagram of the Hopfield Network
pagenum: 219; label: 19.3
title: Storage Capacity of Nonlinear Neural Networks
pagenum: 223; label: 19.4
title: The Dynamics of Pattern Retrieval
pagenum: 226; label: 19.4.1
title: Asymmetric Networks
pagenum: 226; label: 19.4.2
title: Highly Diluted Networks
pagenum: 227; label: 19.4.3
title: The Fully Coupled Network
pagenum: 228; label: 20
title: The Space of Interactions in Neural Networks
pagenum: 231; label: 20.1
title: Replica Solution of the Spherical Model
pagenum: 234; label: 20.2
title: Results
pagenum: 239; label: Part III
title: Computer Codes; label: 21
title: Numerical Demonstrations
pagenum: 249; label: 21.1
title: How to Use the Computer Programs
pagenum: 249; label: 21.2
title: Notes on the Software Implementation
pagenum: 251; label: 22
title: Asso: Associative Memory
pagenum: 253; label: 22.1
title: Program Description
pagenum: 255; label: 22.2
title: Numerical Experiments
pagenum: 259; label: 23
title: Asscount: Associative Memory for Time Sequences
pagenum: 264; label: 23.1
title: Program Description
pagenum: 265; label: 23.2
title: Numerical Experiments
pagenum: 266; label: 24
title: Perbool: Learning Boolean Functions with Back-Prop
pagenum: 268; label: 24.1
title: Program Description
pagenum: 270; label: 24.2
title: Numerical Experiments
pagenum: 272; label: 25
title: Perfunc: Learning Continuous Functions with Back-Prop
pagenum: 275; label: 25.1
title: Program Description
pagenum: 275; label: 25.2
title: Numerical Experiments
pagenum: 277; label: 26
title: Solution of the Traveling-Salesman Problem
pagenum: 279; label: 26.1
title: The Hopfield-Tank Model
pagenum: 279; label: 26.1.1
title: TSPHop: Program Description
pagenum: 281; label: 26.2
title: The Potts-Glass Model
pagenum: 283; label: 26.2.1
title: The Mean-Field Approximation of the Potts Model
pagenum: 284; label: 26.2.2
title: TSPOtts: Program Description
pagenum: 286; label: 26.3
title: TSAnneal: Simulated Annealing
pagenum: 287; label: 26.4
title: Numerical Experiments
pagenum: 289; label: 27
title: Kohomap: The Kohonen Self-Organizing Map
pagenum: 291; label: 27.1
title: Program Description
pagenum: 292; label: 27.2
title: Numerical Experiments
pagenum: 294; label: 28
title: BTT: Back-Propagation Through Time
pagenum: 296; label: 28.1
title: Program Description
pagenum: 297; label: 28.2
title: Numerical Experiments
pagenum: 300; label: 29
title: Neurogen: Using Genetic Algorithms to Train Networks
pagenum: 303; label: 29.1
title: Program Description
pagenum: 303; title: References
pagenum: 307; title: Index
pagenum: 325