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Tables of Contents for Pattern Recognition
Chapter/Section Title
Page #
Page Count
Foreword
vii
Preface
ix
Pattern Recognition: Evolution of Methodologies and Data Mining
1
24
Introduction
2
1
The pattern recognition problem
3
2
The statistical approach
5
3
The syntactic approach
8
1
Classification trees
9
1
The fuzzy set theoretic approach
10
2
The connectionist approach
12
2
Use of genetic algorithms
14
1
The hybrid approach and soft computing
15
1
Data mining and knowledge discovery
16
2
Conclusions
18
7
Imperfect Supervision in Statistical Pattern Recognition
25
42
Statistical pattern recognition
26
4
Preliminaries
30
8
Unsupervised learning
38
7
Models for imperfect supervision
45
4
Effect of imperfect supervision
49
3
Learning with an unreliable supervisor
52
3
Learning with a stochastic supervisor
55
12
Adaptive Stochastic Algorithms for Pattern Classification
67
48
Introduction
67
8
Learning automata
75
7
A common payoff game of automata for pattern classification
82
11
Three layer network consisting of teams of automata for pattern classification
93
10
Modules of learning automata
103
4
Discussion
107
8
Unsupervised Classification: Some Bayesian Approaches
115
32
Introduction
115
2
Finite mixtures of probability distributions
117
2
Bayesian approaches for mixture decomposition
119
14
Discussion
133
14
Shape in Images
147
22
High-level Bayesian image analysis
148
1
Prior models for objects
149
5
Inference
154
3
Multiple objects and occlusions
157
2
Warping and image averaging
159
2
Discussion
161
8
Decision Trees for Classification: A Review and Some New Results
169
16
Introduction
169
2
The different node splitting criteria
171
3
Pruning
174
2
Look-ahead
176
1
Other issues in decision tree construction
176
1
A new look-ahead criterion: some new results
177
4
Conclusions
181
4
Syntactic Pattern Recognition
185
46
Introduction
186
2
Primitive selection strategies
188
2
Formal linguistic model: basic definitions and concepts
190
4
High-dimensional pattern grammars
194
2
Structural recognition of imprecise patterns
196
7
Grammatical inference
203
18
Recognition of ill-formed patterns: error-correcting grammars
221
10
Fuzzy Sets as a Logic Canvas for Pattern Recognition
231
26
Introduction: fuzzy sets and pattern recognition
232
1
Fuzzy set-based transparent topologies of the pattern classifier
233
12
Supervised, unsupervised, and hybrid modes of learning
245
8
Conclusions
253
4
Fuzzy Pattern Recognition by Fuzzy Integrals and Fuzzy Rules
257
24
Introduction
257
1
Classification by fuzzy rules
258
8
Classification by fuzzy integrals
266
15
Neural Network Based Pattern Recognition
281
20
Introduction
281
1
The essence of pattern recognition
282
3
Advanced neural network architectures
285
3
Neural pattern recognition
288
7
Conclusions
295
6
Pattern Classification Based on Quantum Neural Networks: A Case Study
301
28
Introduction
302
1
Quantum neural networks
303
3
Wind profilers
306
3
Formulation of the bird removal problem
309
4
Experimental results
313
12
Conclusions
325
4
Networks of Spiking Neurons in Data Mining
329
18
Introduction
330
2
Graph algorithms
332
4
Clustering
336
4
Critical path method
340
2
The longest common subsequence
342
2
Conclusions
344
3
Genetic Algorithms, Pattern Classification and Neural Networks Design
347
38
Introduction
348
3
Overview of genetic algorithms
351
2
Description of the genetic classifiers
353
13
Determination of MLP architecture
366
9
Discussion and conclusions
375
10
Rough Sets in Pattern Recognition
385
42
Basic rough set approach
385
5
Searching for knowledge
390
26
Hybrid methods
416
1
Conclusions
416
11
Combining Classifiers: Soft Computing Solutions
427
26
Introduction
427
1
Classifier combination
428
6
Soft computing in classifier combination
434
11
Conclusions
445
8
Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods
453
22
Introduction
454
2
Problem
456
4
Approach
460
12
Conclusions
472
3
Neuro-Fuzzy Models for Feature Selection and Classification
475
32
Introduction
475
2
A brief review
477
3
Neuro-fuzzy methods for feature selection
480
10
Neuro-fuzzy knowledge-based classification
490
4
Results
494
3
Conclusions and Discussion
497
10
Adaptive Segmentation Techniques for Hyperspectral Imagery
507
24
Introduction
508
2
Hyperspectral imaging system
510
1
Segmentation of hyperspectral imagery
510
2
Adaptive segmentation based on iterative local feature extraction
512
10
Adaptive unsupervised segmentation
522
6
Conclusions
528
3
Pattern Recognition Issues in Speech Processing
531
28
Introduction
531
4
Nature of speech signal
535
4
Feature extraction in speech
539
2
Pattern recognition models for speech recognition
541
8
Challenges in pattern recognition tasks in speech
549
10
Writing Speed and Writing Sequence Invariant On-Line Handwriting Recognition
559
16
Introduction
559
3
Writing speed invariance
562
6
Writing sequence invariance
568
4
Recognizer
572
1
Conclusions
572
3
Tongue Diagnosis Based on Biometric Pattern Recognition Technology
575
24
Introduction
576
6
Tongue image capturing
582
1
Segmentation of tongue images
583
7
Tongue feature extraction
590
4
Tongue classification
594
1
Conclusions
595
4
Index
599
12
About the editors
611