Neuro-Fuzzy and Soft Computing
Subtitle: A Computational Approach to Learning and Machine Intelligence
Publisher: Prentice Hall
Published: September 26, 1996
Language: eng
Number of pages: 614
ISBN-13: 9780132610667
Description: xxvi, 614 p. : 24 cm
Table of contents: title: Foreword
pagenum: xv; title: Preface
pagenum: xix; label: 1
title: Audience
pagenum: xix; label: 2
title: Organization
pagenum: xx; label: 3
title: Features
pagenum: xxii; label: 4
title: Obtaining the Example Programs
pagenum: xxiii; label: 5
title: Acknowledgments
pagenum: xxiv; label: 6
title: How to Contact Us
pagenum: xxvi; label: 1
title: Introduction to Neuro-Fuzzy and Soft Computing
pagenum: 1; label: 1.1
title: Introduction
pagenum: 1; label: 1.2
title: Soft Computing Constituents and Conventional Artificial Intelligence
pagenum: 1; label: 1.2.1
title: From Conventional AI to Computational Intelligence
pagenum: 3; label: 1.2.2
title: Neural Networks
pagenum: 6; label: 1.2.3
title: Fuzzy Set Theory
pagenum: 6; label: 1.2.4
title: Evolutionary Computation
pagenum: 7; label: 1.3
title: Neuro-Fuzzy and Soft Computing Characteristics
pagenum: 7; label: I
title: Fuzzy Set Theory
pagenum: 11; label: 2
title: Fuzzy Sets
pagenum: 13; label: 2.1
title: Introduction
pagenum: 13; label: 2.2
title: Basic Definitions and Terminology
pagenum: 14; label: 2.3
title: Set-Theoretic Operations
pagenum: 21; label: 2.4
title: Mf Formulation and Parameterization
pagenum: 24; label: 2.4.1
title: Mfs of One Dimension
pagenum: 24; label: 2.4.2
title: Mfs of Two Dimensions
pagenum: 30; label: 2.4.3
title: Derivatives of Parameterized Mfs
pagenum: 34; label: 2.5
title: More on Fuzzy Union, Intersection, and Complement*
pagenum: 35; label: 2.5.1
title: Fuzzy Complement*
pagenum: 35; label: 2.5.2
title: Fuzzy Intersection and Union*
pagenum: 36; label: 2.5.3
title: Parameterized T-norm and T-conorm*
pagenum: 40; label: 2.6
title: Summary
pagenum: 42; title: Exercises
pagenum: 42; label: 3
title: Fuzzy Rules and Fuzzy Reasoning
pagenum: 47; label: 3.1
title: Introduction
pagenum: 47; label: 3.2
title: Extension Principle and Fuzzy Relations
pagenum: 47; label: 3.2.1
title: Extension Principle
pagenum: 47; label: 3.2.2
title: Fuzzy Relations
pagenum: 50; label: 3.3
title: Fuzzy If-Then Rules
pagenum: 54; label: 3.3.1
title: Linguistic Variables
pagenum: 54; label: 3.3.2
title: Fuzzy If-Then Rules
pagenum: 59; label: 3.4
title: Fuzzy Reasoning
pagenum: 62; label: 3.4.1
title: Compositional Rule of Inference
pagenum: 63; label: 3.4.2
title: Fuzzy Reasoning
pagenum: 64; label: 3.5
title: Summary
pagenum: 70; title: Exercises
pagenum: 70; label: 4
title: Fuzzy Inference Systems
pagenum: 73; label: 4.1
title: Introduction
pagenum: 73; label: 4.2
title: Mamdani Fuzzy Models
pagenum: 74; label: 4.2.1
title: Other Variants
pagenum: 79; label: 4.3
title: Sugeno Fuzzy Models
pagenum: 81; label: 4.4
title: Tsukamoto Fuzzy Models
pagenum: 84; label: 4.5
title: Other Considerations
pagenum: 85; label: 4.5.1
title: Input Space Partitioning
pagenum: 86; label: 4.5.2
title: Fuzzy Modeling
pagenum: 87; label: 4.6
title: Summary
pagenum: 89; title: Exercises
pagenum: 90; label: II
title: Regression and Optimization
pagenum: 93; label: 5
title: Least-Squares Methods for System Identification
pagenum: 95; label: 5.1
title: System Identification: An Introduction
pagenum: 95; label: 5.2
title: Basics of Matrix Manipulation and Calculus
pagenum: 97; label: 5.3
title: Least-Squares Estimator
pagenum: 104; label: 5.4
title: Geometric Interpretation of LSE
pagenum: 110; label: 5.5
title: Recursive Least-Squares Estimator
pagenum: 113; label: 5.6
title: Recursive LSE for Time-Varying Systems*
pagenum: 116; label: 5.7
title: Statistical Properties and the Maximum Likelihood Estimator*
pagenum: 118; label: 5.8
title: LSE for Nonlinear Models
pagenum: 122; label: 5.9
title: Summary
pagenum: 125; title: Exercises
pagenum: 126; label: 6
title: Derivative-Based Optimization
pagenum: 129; label: 6.1
title: Introduction
pagenum: 129; label: 6.2
title: Descent Methods
pagenum: 129; label: 6.2.1
title: Gradient-Based Methods
pagenum: 130; label: 6.3
title: The Method of Steepest Descent
pagenum: 133; label: 6.4
title: Newton's Methods
pagenum: 134; label: 6.4.1
title: Classical Newton's Method
pagenum: 134; label: 6.4.2
title: Modified Newton's Methods*
pagenum: 136; label: 6.4.3
title: Quasi-Newton Methods*
pagenum: 139; label: 6.5
title: Step Size Determination
pagenum: 141; label: 6.5.1
title: Initial Bracketing
pagenum: 141; label: 6.5.2
title: Line Searches
pagenum: 142; label: 6.5.3
title: Termination Rules*
pagenum: 146; label: 6.6
title: Conjugate Gradient Methods*
pagenum: 148; label: 6.6.1
title: Conjugate Directions*
pagenum: 148; label: 6.6.2
title: From Orthogonality to Conjugacy*
pagenum: 149; label: 6.6.3
title: Conjugate Gradient Algorithms*
pagenum: 152; label: 6.7
title: Analysis of Quadratic Case
pagenum: 154; label: 6.7.1
title: Descent Methods with Line Minimization
pagenum: 156; label: 6.7.2
title: Steepest Descent Method without Line Minimization
pagenum: 156; label: 6.8
title: Nonlinear Least-Squares Problems
pagenum: 160; label: 6.8.1
title: Gauss-Newton Method
pagenum: 161; label: 6.8.2
title: Levenberg-Marquardt Concepts
pagenum: 163; label: 6.9
title: Incorporation of Stochastic Mechanisms
pagenum: 166; label: 6.10
title: Summary
pagenum: 168; title: Exercises
pagenum: 168; label: 7
title: Derivative-Free Optimization
pagenum: 173; label: 7.1
title: Introduction
pagenum: 173; label: 7.2
title: Genetic Algorithms
pagenum: 175; label: 7.3
title: Simulated Annealing
pagenum: 181; label: 7.4
title: Random Search
pagenum: 186; label: 7.5
title: Downhill Simplex Search
pagenum: 189; label: 7.6
title: Summary
pagenum: 193; title: Exercises
pagenum: 194; label: III
title: Neural Networks
pagenum: 197; label: 8
title: Adaptive Networks
pagenum: 199; label: 8.1
title: Introduction
pagenum: 199; label: 8.2
title: Architecture
pagenum: 200; label: 8.3
title: Backpropagation for Feedforward Networks
pagenum: 205; label: 8.4
title: Extended Backpropagation for Recurrent Networks
pagenum: 210; label: 8.4.1
title: Synchronously Operated Networks: BPTT and RTRL
pagenum: 212; label: 8.4.2
title: Continuously Operated Networks: Mason's Gain Formula*
pagenum: 215; label: 8.5
title: Hybrid Learning Rule: Combining Steepest Descent and LSE
pagenum: 219; label: 8.5.1
title: Off-Line Learning (Batch Learning)
pagenum: 220; label: 8.5.2
title: On-Line Learning (Pattern-By-Pattern Learning)
pagenum: 222; label: 8.5.3
title: Different Ways of Combining Steepest Descent and LSE
pagenum: 222; label: 8.6
title: Summary
pagenum: 223; title: Exercises
pagenum: 223; label: 9
title: Supervised Learning Neural Networks
pagenum: 226; label: 9.1
title: Introduction
pagenum: 226; label: 9.2
title: Perceptrons
pagenum: 227; label: 9.2.1
title: Architecture and Learning Rule
pagenum: 227; label: 9.2.2
title: Exclusive-OR Problem
pagenum: 229; label: 9.3
title: Adaline
pagenum: 230; label: 9.4
title: Backpropagation Multilayer Perceptrons
pagenum: 233; label: 9.4.1
title: Backpropagation Learning Rule
pagenum: 234; label: 9.4.2
title: Methods of Speeding Up MLP Training
pagenum: 236; label: 9.4.3
title: MLP's Approximation Power
pagenum: 238; label: 9.5
title: Radial Basis Function Networks
pagenum: 238; label: 9.5.1
title: Architectures and Learning Methods
pagenum: 238; label: 9.5.2
title: Functional Equivalence to FIS
pagenum: 241; label: 9.5.3
title: Interpolation and Approximation RBFNs
pagenum: 242; label: 9.5.4
title: Examples
pagenum: 244; label: 9.6
title: Modular Networks
pagenum: 246; label: 9.7
title: Summary
pagenum: 250; title: Exercises
pagenum: 251; label: 10
title: Learning from Reinforcement
pagenum: 258; label: 10.1
title: Introduction
pagenum: 258; label: 10.2
title: Failure Is the Surest Path to Success
pagenum: 259; label: 10.2.1
title: Jackpot Journey
pagenum: 259; label: 10.2.2
title: Credit Assignment Problem
pagenum: 262; label: 10.2.3
title: Evaluation Functions
pagenum: 263; label: 10.3
title: Temporal Difference Learning
pagenum: 264; label: 10.3.1
title: TD Formulation
pagenum: 265; label: 10.3.2
title: Expected Jackpot
pagenum: 266; label: 10.3.3
title: Predicting Cumulative Outcomes
pagenum: 268; label: 10.4
title: The Art of Dynamic Programming
pagenum: 270; label: 10.4.1
title: Formulation of Classical Dynamic Programming
pagenum: 270; label: 10.4.2
title: Incremental Dynamic Programming
pagenum: 272; label: 10.5
title: Adaptive Heuristic Critic
pagenum: 273; label: 10.5.1
title: Neuron-like Critic
pagenum: 273; label: 10.5.2
title: An Adaptive Neural Critic Algorithm
pagenum: 274; label: 10.5.3
title: Exploration and Action Selection
pagenum: 277; label: 10.6
title: Q-learning
pagenum: 278; label: 10.6.1
title: Basic Concept
pagenum: 278; label: 10.6.2
title: Implementation
pagenum: 279; label: 10.7
title: A Cost Path Problem
pagenum: 281; label: 10.7.1
title: Expected Cost Path Problem by TD Methods
pagenum: 282; label: 10.7.2
title: Finding an Optimal Path in a Deterministic Minimum Cost Path Problem
pagenum: 283; label: 10.7.3
title: State Representations for Generalization
pagenum: 287; label: 10.8
title: World Modeling*
pagenum: 288; label: 10.8.1
title: Model-free and Model-based Learning*
pagenum: 288; label: 10.8.2
title: Distal Teacher*
pagenum: 289; label: 10.8.3
title: Learning Speed*
pagenum: 289; label: 10.9
title: Other Network Configurations*
pagenum: 290; label: 10.9.1
title: Divide-and-Conquer Methodology*
pagenum: 290; label: 10.9.2
title: Recurrent Networks*
pagenum: 291; label: 10.10
title: Reinforcement Learning by Evolutionary Computation*
pagenum: 292; label: 10.10.1
title: Bucket Brigade*
pagenum: 292; label: 10.10.2
title: Genetic Reinforcers*
pagenum: 292; label: 10.10.3
title: Immune Modeling*
pagenum: 293; label: 10.11
title: Summary
pagenum: 293; title: Exercises
pagenum: 294; label: 11
title: Unsupervised Learning and Other Neural Networks
pagenum: 301; label: 11.1
title: Introduction
pagenum: 301; label: 11.2
title: Competitive Learning Networks
pagenum: 302; label: 11.3
title: Kohonen Self-Organizing Networks
pagenum: 305; label: 11.4
title: Learning Vector Quantization
pagenum: 308; label: 11.5
title: Hebbian Learning
pagenum: 310; label: 11.6
title: Principal Component Networks
pagenum: 312; label: 11.6.1
title: Principal Component Analysis
pagenum: 312; label: 11.6.2
title: Oja's Modified Hebbian Rule
pagenum: 316; label: 11.7
title: The Hopfield Network
pagenum: 316; label: 11.7.1
title: Content-Addressable Nature
pagenum: 317; label: 11.7.2
title: Binary Hopfield Networks
pagenum: 318; label: 11.7.3
title: Continuous-Valued Hopfield Networks
pagenum: 321; label: 11.7.4
title: Traveling Salesperson Problem
pagenum: 324; label: 11.7.5
title: The Boltzmann Machine
pagenum: 326; label: 11.8
title: Summary
pagenum: 327; title: Exercises
pagenum: 328; label: IV
title: Neuro-Fuzzy Modeling
pagenum: 333; label: 12
title: ANFIS: Adaptive Neuro-Fuzzy Inference Systems
pagenum: 335; label: 12.1
title: Introduction
pagenum: 335; label: 12.2
title: ANFIS Architecture
pagenum: 336; label: 12.3
title: Hybrid Learning Algorithm
pagenum: 340; label: 12.4
title: Learning Methods that Cross-fertilize ANFIS and RBFN
pagenum: 341; label: 12.5
title: ANFIS as a Universal Approximator*
pagenum: 342; label: 12.6
title: Simulation Examples
pagenum: 345; label: 12.6.1
title: Practical Considerations
pagenum: 345; label: 12.6.2
title: Example 1: Modeling a Two-Input Sinc Function
pagenum: 346; label: 12.6.3
title: Example 2: Modeling a Three-Input Nonlinear Function
pagenum: 348; label: 12.6.4
title: Example 3: On-Line Identification in Control Systems
pagenum: 351; label: 12.6.5
title: Example 4: Predicting Chaotic Time Series
pagenum: 353; label: 12.7
title: Extensions and Advanced Topics
pagenum: 360; title: Exercises
pagenum: 363; label: 13
title: Coactive Neuro-Fuzzy Modeling: Towards Generalized ANFIS
pagenum: 369; label: 13.1
title: Introduction
pagenum: 369; label: 13.2
title: Framework
pagenum: 370; label: 13.2.1
title: Toward Multiple Inputs/Outputs Systems
pagenum: 370; label: 13.2.2
title: Architectural Comparisons
pagenum: 370; label: 13.3
title: Neuron Functions for Adaptive Networks
pagenum: 372; label: 13.3.1
title: Fuzzy Membership Functions versus Receptive Field Units
pagenum: 373; label: 13.3.2
title: Nonlinear Rule
pagenum: 376; label: 13.3.3
title: Modified Sigmoidal and Truncation Filter Functions
pagenum: 380; label: 13.4
title: Neuro-Fuzzy Spectrum
pagenum: 382; label: 13.5
title: Analysis of Adaptive Learning Capability
pagenum: 385; label: 13.5.1
title: Convergence Based on the Steepest Descent Method Alone
pagenum: 385; label: 13.5.2
title: Interpretability Spectrum
pagenum: 386; label: 13.5.3
title: Evolution of Antecedents (Mfs)
pagenum: 387; label: 13.5.4
title: Evolution of Consequents (Rules)
pagenum: 389; label: 13.5.5
title: Evolving Partitions
pagenum: 390; label: 13.6
title: Summary
pagenum: 393; title: Exercises
pagenum: 395; label: V
title: Advanced Neuro-Fuzzy Modeling
pagenum: 401; label: 14
title: Classification and Regression Trees
pagenum: 403; label: 14.1
title: Introduction
pagenum: 403; label: 14.2
title: Decision Trees
pagenum: 404; label: 14.3
title: CART Algorithm for Tree Induction
pagenum: 406; label: 14.3.1
title: Tree Growing
pagenum: 407; label: 14.3.2
title: Tree Pruning
pagenum: 413; label: 14.4
title: Using CART for Structure Identification in ANFIS
pagenum: 416; label: 14.5
title: Summary
pagenum: 421; title: Exercises
pagenum: 421; label: 15
title: Data Clustering Algorithms
pagenum: 423; label: 15.1
title: Introduction
pagenum: 423; label: 15.2
title: K-Means Clustering
pagenum: 424; label: 15.3
title: Fuzzy C-Means Clustering
pagenum: 425; label: 15.4
title: Mountain Clustering Method
pagenum: 427; label: 15.5
title: Subtractive Clustering
pagenum: 431; label: 15.6
title: Summary
pagenum: 432; title: Exercises
pagenum: 432; label: 16
title: Rulebase Structure Identification
pagenum: 434; label: 16.1
title: Introduction
pagenum: 434; label: 16.2
title: Input Selection
pagenum: 435; label: 16.3
title: Input Space Partitioning
pagenum: 436; label: 16.4
title: Rulebase Organization
pagenum: 441; label: 16.5
title: Focus Set-Based Rule Combination
pagenum: 446; label: 16.6
title: Summary
pagenum: 447; title: Exercises
pagenum: 448; label: VI
title: Neuro-Fuzzy Control
pagenum: 451; label: 17
title: Neuro-Fuzzy Control I
pagenum: 453; label: 17.1
title: Introduction
pagenum: 453; label: 17.2
title: Feedback Control Systems and Neuro-Fuzzy Control: An Overview
pagenum: 454; label: 17.2.1
title: Feedback Control Systems
pagenum: 454; label: 17.2.2
title: Neuro-Fuzzy Control
pagenum: 458; label: 17.3
title: Expert Control: Mimicking an Expert
pagenum: 458; label: 17.4
title: Inverse Learning
pagenum: 460; label: 17.4.1
title: Fundamentals
pagenum: 460; label: 17.4.2
title: Case Studies
pagenum: 463; label: 17.5
title: Specialized Learning
pagenum: 465; label: 17.6
title: Backpropagation Through Time and Real-Time Recurrent Learning
pagenum: 469; label: 17.6.1
title: Fundamentals
pagenum: 469; label: 17.6.2
title: Case Studies: The Inverted Pendulum System
pagenum: 470; label: 17.7
title: Summary
pagenum: 476; title: Exercises
pagenum: 477; label: 18
title: Neuro-Fuzzy Control II
pagenum: 480; label: 18.1
title: Introduction
pagenum: 480; label: 18.2
title: Reinforcement Learning Control
pagenum: 480; label: 18.2.1
title: Control Environment
pagenum: 480; label: 18.2.2
title: Neuro-Fuzzy Reinforcement Controllers
pagenum: 481; label: 18.3
title: Gradient-Free Optimization
pagenum: 483; label: 18.3.1
title: GAs: Coding and Genetic Operators
pagenum: 484; label: 18.3.2
title: GAs: Formulating Objective Functions
pagenum: 488; label: 18.4
title: Gain Scheduling
pagenum: 489; label: 18.4.1
title: Fundamentals
pagenum: 489; label: 18.4.2
title: Case Studies
pagenum: 491; label: 18.5
title: Feedback Linearization and Sliding Control
pagenum: 493; label: 18.6
title: Summary
pagenum: 496; title: Exercises
pagenum: 497; label: VII
title: Advanced Applications
pagenum: 501; label: 19
title: ANFIS Applications
pagenum: 503; label: 19.1
title: Introduction
pagenum: 503; label: 19.2
title: Printed Character Recognition
pagenum: 503; label: 19.3
title: Inverse Kinematics Problems
pagenum: 507; label: 19.4
title: Automobile MPG Prediction
pagenum: 510; label: 19.5
title: Nonlinear System Identification
pagenum: 514; label: 19.6
title: Channel Equalization
pagenum: 516; label: 19.7
title: Adaptive Noise Cancellation
pagenum: 523; label: 20
title: Fuzzy-Filtered Neural Networks
pagenum: 535; label: 20.1
title: Introduction
pagenum: 535; label: 20.2
title: Fuzzy-Filtered Neural Networks
pagenum: 536; label: 20.3
title: Application 1: Plasma Spectrum Analysis
pagenum: 538; label: 20.3.1
title: Multilayer Perceptron Approach
pagenum: 538; label: 20.3.2
title: Fuzzy-Filtered Neural Network Approach
pagenum: 539; label: 20.4
title: Application 2: Hand-Written Numeral Recognition
pagenum: 540; label: 20.4.1
title: One Dimensional Fuzzy Filters
pagenum: 541; label: 20.4.2
title: Two Dimensional Fuzzy Filters
pagenum: 542; label: 20.5
title: Genetic Algorithm-Based Fuzzy Filters
pagenum: 543; label: 20.5.1
title: A General Model
pagenum: 543; label: 20.5.2
title: Variations and Discussion
pagenum: 545; label: 20.6
title: Summary
pagenum: 549; label: 21
title: Fuzzy Sets and Genetic Algorithms in Game Playing
pagenum: 551; label: 21.1
title: Introduction
pagenum: 551; label: 21.2
title: Variants of Genetic Algorithms
pagenum: 551; label: 21.3
title: Using Genetic Algorithms in Game Playing
pagenum: 553; label: 21.4
title: Simulation Results of the Basic Model
pagenum: 556; label: 21.5
title: Using Fuzzily Characterized Features
pagenum: 559; label: 21.6
title: Using Polyploid GA in Game Playing
pagenum: 560; label: 21.7
title: Summary
pagenum: 564; label: 22
title: Soft Computing for Color Recipe Prediction
pagenum: 568; label: 22.1
title: Introduction
pagenum: 568; label: 22.2
title: Color Recipe Prediction
pagenum: 569; label: 22.3
title: Single MLP Approaches
pagenum: 569; label: 22.4
title: CANFIS Modeling for Color Recipe Prediction
pagenum: 571; label: 22.4.1
title: Fuzzy Partitionings
pagenum: 572; label: 22.4.2
title: CANFIS Architectures
pagenum: 573; label: 22.4.3
title: Knowledge-Embedded Structures
pagenum: 576; label: 22.4.4
title: CANFIS Simulation
pagenum: 576; label: 22.5
title: Color Paint Manufacturing Intelligence
pagenum: 577; label: 22.5.1
title: Manufacturing Intelligence Architecture
pagenum: 579; label: 22.5.2
title: Knowledge Base
pagenum: 580; label: 22.5.3
title: Multi-elites Generator
pagenum: 581; label: 22.5.4
title: Fuzzy Population Generator
pagenum: 581; label: 22.5.5
title: Fitness Function
pagenum: 582; label: 22.5.6
title: Genetic Strategies
pagenum: 584; label: 22.6
title: Experimental Evaluation
pagenum: 587; label: 22.7
title: Discussion
pagenum: 589; label: 22.8
title: Concluding Remarks and Future Directions
pagenum: 591; label: A
title: Hints to Selected Exercises
pagenum: 595; label: B
title: List of Internet Resources
pagenum: 598; label: C
title: List of MATLAB Programs
pagenum: 601; label: D
title: List of Acronyms
pagenum: 604; title: Index
pagenum: 607