Co-publication with Universities Press (India) Pvt. Ltd.
2011, XII, 263p.
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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
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.
Content Level »Upper undergraduate
Keywords »Bayes Classifier - Combinational Classifiers - Decision Trees - Hidden Markov Models - Hierarchical and Partitioning Schemes for Clustering - Nearest Neighbour Classifiers - Support Vector Machine
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