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Monday, July 27, 2020 | History

14 edition of Introduction to statistical pattern recognition found in the catalog.

Introduction to statistical pattern recognition

by Keinosuke Fukunaga

  • 98 Want to read
  • 30 Currently reading

Published by Academic Press in Boston .
Written in English

    Subjects:
  • Pattern perception -- Statistical methods.,
  • Decision making -- Mathematical models.,
  • Mathematical statistics.

  • Edition Notes

    Includes bibliographical references and index.

    StatementKeinosuke Fukunaga.
    SeriesComputer science and scientific computing
    Classifications
    LC ClassificationsQ327 .F85 1990
    The Physical Object
    Paginationxiii, 591 p. :
    Number of Pages591
    ID Numbers
    Open LibraryOL2198420M
    ISBN 100122698517
    LC Control Number89018195

    Introduction. Pattern recognition techniques are used to automatically classify physical objects (handwritten characters, tissue samples, faces) or abstract multidimensional patterns (n points in d dimensions) into known or possibly unknown number of categories.A number of commercial pattern recognition systems are available for character recognition, signature recognition, document. Introduction to Statistical Pattern Recognition (Computer Science & Scientific Computing) by Keinosuke Fukunaga and a great selection of related books, art .

      Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises. show more/5(14). This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications.4/5(1).

    Introduction to Statistical Pattern Recognition: Fukunaga, Keinosuke: Books - (4). PATTERN RECOGNITION Robi Polikar (Rowan University) Statistical Pattern Recognition Dongil Shin (Sejong University) Statistical Pattern Recognition: A Review Anil K. Jain (Fellow, IEEE), Robert P.W. Duin, and Jianchang Mao (Senior Member, IEEE) Introduction to Statistical Learning Theory Olivier Bousquet, Stephane Boucheron, and Gabor Lugosi.


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Introduction to statistical pattern recognition by Keinosuke Fukunaga Download PDF EPUB FB2

Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises/5(7).

Statistical pattern recognition Introduction This book describes basic pattern recognition procedures, together with practical appli-cations of the techniques on real-world problems.

A strong emphasis is placed on the statistical theory of discrimination, but. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition.

This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises. This completely revised second edition presents an introduction to statistical pattern recognition.

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Includes new material presenting the analysis of complex networks. Introduces readers to methods for Bayesian density estimation. Statistical pattern recognition 1 Introduction 1 The basic model 2 Stages in a pattern recognition problem 3 Issues 4 Supervised versus unsupervised 5 Approaches to statistical pattern recognition 6 Elementary decision theory 6 Discriminant functions 19 Multiple regression 25 Outline of book.

Introduction to Statistical Pattern Recognition, 2nd ed, Keinosuke Fukunaga, Academic Press, Learning in Neural Networks: Theoretical Foundations, M. Anthony and P. Bartlett, Cambridge University Press,   Statistical pattern recognition is a very active area of study and research, which has seen many advances in recent years.

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Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.

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Pattern Recognition by Prof. P.S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore.

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