Introduction to Pattern Recognition A MATLAB� Approach

ISBN-10: 0123744865
ISBN-13: 9780123744869
Edition: 2009
List price: $41.95 Buy it from $24.00 Rent it from $18.11
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Description: Matlab booklet to accompany Theodoridis, Pattern Recognition 4e. Contains tutorials, examples, and Matlab code corresponding to chapters from the Pattern Recognition text.

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Book details

List price: $41.95
Copyright year: 2009
Publisher: Elsevier Science & Technology Books
Publication date: 3/17/2010
Binding: Paperback
Pages: 231
Size: 7.75" wide x 9.50" long x 0.75" tall
Weight: 0.924
Language: English

Matlab booklet to accompany Theodoridis, Pattern Recognition 4e. Contains tutorials, examples, and Matlab code corresponding to chapters from the Pattern Recognition text.

Preface
Classifiers Based on Bayes Decision Theory
Introduction
Bayes Decision Theory
The Gaussian Probability Density Function
Minimum Distance Classifiers
The Euclidean Distance Classifier
The Mahalanobis Distance Classifier
Maximum Likelihood Parameter Estimation of Gaussian pdfs
Mixture Models
The Expectation-Maximization Algorithm
Parzen Windows
k-Nearest Neighbor Density Estimation
The Naive Bayes Classifier
The Nearest Neighbor Rule
Classifiers Based on Cost Function Optimization
Introduction
The Perceptron Algorithm
The Online Form of the Perceptron Algorithm
The Sum of Error Squares Classifier
The Multiclass LS Classifier
Support Vector Machines: The Linear Case
Multiclass Generalizations
SVM: The Nonlinear Case
The Kernel Perceptron Algorithm
The AdaBoost Algorithm
Multilayer Perceptrons
Data Transformation: Feature Generation and Dimensionality Reduction
Introduction
Principal Component Analysis
The Singular Value Decomposition Method
Fisher's Linear Discriminant Analysis
The Kernel PCA
Laplacian Eigenmap
Feature Selection
Introduction
Outlier Removal
Data Normalization
Hypothesis Testing: The t-Test
The Receiver Operating Characteristic Curve
Fisher's Discriminant Ratio
Class Separability Measures
Divergence
Bhattacharyya Distance and Chernoff Bound
Measures Based on Scatter Matrices
Feature Subset Selection
Scalar Feature Selection
Feature Vector Selection
Template Matching
Introduction
The Edit Distance
Matching Sequences of Real Numbers
Dynamic Time Warping in Speech Recognition
Hidden Markov Models
Introduction
Modeling
Recognition and Training
Clustering
Introduction
Basic Concepts and Definitions
Clustering Algorithms
Sequential Algorithms
BSAS Algorithm
Clustering Refinement
Cost Function Optimization Clustering Algorithms
Hard Clustering Algorithms
Nonhard Clustering Algorithms
Miscellaneous Clustering Algorithms
Hierarchical Clustering Algorithms
Generalized Agglomerative Scheme
Specific Agglomerative Clustering Algorithms
Choosing the Best Clustering
Appendix
References
Index

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