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© 2011

Pattern Recognition

An Algorithmic Approach

  • Contains numerous exercises, as well as learning objectives and summaries for each chapter

  • Explains the hidden Markov model for speech and speaker recognition tasks

  • Discusses support vector machines, with suitable examples

Textbook

Part of the Undergraduate Topics in Computer Science book series (UTICS, volume 0)

Table of contents

  1. Front Matter
    Pages I-XI
  2. M. Narasimha Murty, V. Susheela Devi
    Pages 1-6
  3. M. Narasimha Murty, V. Susheela Devi
    Pages 7-47
  4. M. Narasimha Murty, V. Susheela Devi
    Pages 48-85
  5. M. Narasimha Murty, V. Susheela Devi
    Pages 86-102
  6. M. Narasimha Murty, V. Susheela Devi
    Pages 103-122
  7. M. Narasimha Murty, V. Susheela Devi
    Pages 123-146
  8. M. Narasimha Murty, V. Susheela Devi
    Pages 147-187
  9. M. Narasimha Murty, V. Susheela Devi
    Pages 188-206
  10. M. Narasimha Murty, V. Susheela Devi
    Pages 207-244
  11. M. Narasimha Murty, V. Susheela Devi
    Pages 245-246
  12. M. Narasimha Murty, V. Susheela Devi
    Pages 247-254
  13. Back Matter
    Pages 255-263

About this book

Introduction

Observing the environment, and recognising patterns for the purpose of decision-making, is fundamental to human nature. The scientific discipline of pattern recognition (PR) is devoted to how machines use computing to discern patterns in the real world.

This must-read textbook provides an exposition of principal topics in PR using an algorithmic approach. Presenting a thorough introduction to the concepts of PR and a systematic account of the major topics, the text also reviews the vast progress made in the field in recent years. The algorithmic approach makes the material more accessible to computer science and engineering students.

Topics and features:

  • Makes thorough use of examples and illustrations throughout the text, and includes end-of-chapter exercises and suggestions for further reading
  • Describes a range of classification methods, including nearest-neighbour classifiers, Bayes classifiers, and decision trees
  • Includes chapter-by-chapter learning objectives and summaries, as well as extensive referencing
  • Presents standard tools for machine learning and data mining, covering neural networks and support vector machines that use discriminant functions
  • Explains important aspects of PR in detail, such as clustering
  • Discusses hidden Markov models for speech and speaker recognition tasks, clarifying core concepts through simple examples

This concise and practical text/reference will perfectly meet the needs of senior undergraduate and postgraduate students of computer science and related disciplines. Additionally, the book will be useful to all researchers who need to apply PR techniques to solve their problems.

Dr. M. Narasimha Murty is a Professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore. Dr. V. Susheela Devi is a Senior Scientific Officer at the same institution.

Keywords

Bayes Classifier Combinational Classifiers Decision Trees Hidden Markov Models Hierarchical and Partitioning Schemes for Clustering Nearest Neighbour Classifiers Support Vector Machine

Authors and affiliations

  1. 1.Dept. of Computer Science and AutomationIndian Institute of ScienceBangaloreIndia

About the authors

Dr. M. Narasimha Murty is a professor in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore. Dr. V. Susheela Devi is a senior scientific officer in the Department of Computer Science and Automation at the Indian Institute of Science, Bangalore.

Bibliographic information

  • Book Title Pattern Recognition
  • Book Subtitle An Algorithmic Approach
  • Authors M. Narasimha Murty
    V. Susheela Devi
  • Series Title Undergraduate Topics in Computer Science
  • DOI https://doi.org/10.1007/978-0-85729-495-1
  • Copyright Information Universities Press (India) Pvt. Ltd. 2011
  • Publisher Name Springer, London
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-0-85729-494-4
  • eBook ISBN 978-0-85729-495-1
  • Series ISSN 1863-7310
  • Edition Number 1
  • Number of Pages XI, 263
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Additional Information Co-publication with Universities Press (India) Pvt. Ltd.
  • Topics Computer Science, general
  • Buy this book on publisher's site
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Reviews

From the reviews:

“This interesting book provides a concise and simple exposition of principal topics in pattern recognition using an algorithmic approach, and is intended mainly for undergraduate and postgraduate students. … An application to handwritten digit recognition is described at the end of the book. Many examples and exercises are proposed to make the treatment clear. A ‘further reading’ section and a bibliography are presented at the end of each chapter.” (Patrizio Frosini, Zentralblatt MATH, Vol. 1238, 2012)