Items related to Pattern Recognition, Second Edition
*Approaches pattern recognition from the designer's point of view
*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere
*Supplemented by computer examples selected from applications of interest
Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. This volume's unifying treatment covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn". A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.
*Approaches pattern recognition from the designer's point of view
*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere
*Supplemented by computer examples selected from applications of interest
*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere
*Supplemented by computer examples selected from applications of interest
Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. This volume's unifying treatment covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn". A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.
*Approaches pattern recognition from the designer's point of view
*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere
*Supplemented by computer examples selected from applications of interest
"synopsis" may belong to another edition of this title.
Book Description:
A classic that offers comprehensive coverage with a balance between theory and practice.
From the Back Cover:
Pattern recognition is becoming increasingly important in the age of automation and information handling and retrieval.
This book provides the most comprehensive treatment available of pattern recognition, from an engineering perspective. Developed through more than ten years of teaching experience, Pattern Recognition is appropriate for both advanced engineering students and practicing engineers.
Coverage includes:
· Feature generation, including features based on Wavelet Transforms and Fractals.
· Feature selection techniques.
· Design of linear and non linear classifiers, including Bayesian, Multilayer Perceptrons, and RBF networks
. Context-dependent classification, including Dynamic Programming and Hidden Markov Modeling techniques
. Classical approaches, as well as more recent developments in clustering algorithms, such as fuzzy, possibilistic, morphological, genetic, and annealing techniques
. Coverage of numerous, diverse applications, including Image Analysis, Character Recognition, Medical Diagnosis, Speech Recognition, and Channel Equalization
. Numerous computer simulation examples, supporting the methods given in the book, available via the Webb.
This book provides the most comprehensive treatment available of pattern recognition, from an engineering perspective. Developed through more than ten years of teaching experience, Pattern Recognition is appropriate for both advanced engineering students and practicing engineers.
Coverage includes:
· Feature generation, including features based on Wavelet Transforms and Fractals.
· Feature selection techniques.
· Design of linear and non linear classifiers, including Bayesian, Multilayer Perceptrons, and RBF networks
. Context-dependent classification, including Dynamic Programming and Hidden Markov Modeling techniques
. Classical approaches, as well as more recent developments in clustering algorithms, such as fuzzy, possibilistic, morphological, genetic, and annealing techniques
. Coverage of numerous, diverse applications, including Image Analysis, Character Recognition, Medical Diagnosis, Speech Recognition, and Channel Equalization
. Numerous computer simulation examples, supporting the methods given in the book, available via the Webb.
"About this title" may belong to another edition of this title.
- PublisherAcademic Press
- Publication date2003
- ISBN 10 0126858756
- ISBN 13 9780126858754
- BindingHardcover
- Edition number2
- Number of pages689
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Pattern Recognition, Second Edition
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Academic Press
(2003)
ISBN 10: 0126858756
ISBN 13: 9780126858754
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