<?xml version="1.0" encoding="UTF-8"?>
<record
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd"
    xmlns="http://www.loc.gov/MARC21/slim">

  <leader>03590nam a22004335i 4500</leader>
  <controlfield tag="001">978-0-85729-495-1</controlfield>
  <controlfield tag="003">DE-He213</controlfield>
  <controlfield tag="005">20260521092040.0</controlfield>
  <controlfield tag="007">cr nn 008mamaa</controlfield>
  <controlfield tag="008">110525s2011    xxk|    s    |||| 0|eng d</controlfield>
  <datafield tag="020" ind1=" " ind2=" ">
    <subfield code="a">9780857294951</subfield>
  </datafield>
  <datafield tag="020" ind1=" " ind2=" ">
    <subfield code="a">99780857294951</subfield>
  </datafield>
  <datafield tag="024" ind1="7" ind2=" ">
    <subfield code="a">10.1007/978-0-85729-495-1</subfield>
    <subfield code="2">doi</subfield>
  </datafield>
  <datafield tag="082" ind1="0" ind2="4">
    <subfield code="a">004</subfield>
    <subfield code="2">23</subfield>
  </datafield>
  <datafield tag="100" ind1="1" ind2=" ">
    <subfield code="a">Murty, M. Narasimha.</subfield>
    <subfield code="e">author.</subfield>
  </datafield>
  <datafield tag="245" ind1="1" ind2="0">
    <subfield code="a">Pattern Recognition</subfield>
    <subfield code="h">[electronic resource] :</subfield>
    <subfield code="b">An Algorithmic Approach /</subfield>
    <subfield code="c">by M. Narasimha Murty, V. Susheela Devi.</subfield>
  </datafield>
  <datafield tag="250" ind1=" " ind2=" ">
    <subfield code="a">1.</subfield>
  </datafield>
  <datafield tag="264" ind1=" " ind2="1">
    <subfield code="a">London :</subfield>
    <subfield code="b">Springer London,</subfield>
    <subfield code="c">2011.</subfield>
  </datafield>
  <datafield tag="300" ind1=" " ind2=" ">
    <subfield code="a">XII, 263p.</subfield>
    <subfield code="b">online resource.</subfield>
  </datafield>
  <datafield tag="336" ind1=" " ind2=" ">
    <subfield code="a">text</subfield>
    <subfield code="b">txt</subfield>
    <subfield code="2">rdacontent</subfield>
  </datafield>
  <datafield tag="337" ind1=" " ind2=" ">
    <subfield code="a">computer</subfield>
    <subfield code="b">c</subfield>
    <subfield code="2">rdamedia</subfield>
  </datafield>
  <datafield tag="338" ind1=" " ind2=" ">
    <subfield code="a">online resource</subfield>
    <subfield code="b">cr</subfield>
    <subfield code="2">rdacarrier</subfield>
  </datafield>
  <datafield tag="347" ind1=" " ind2=" ">
    <subfield code="a">text file</subfield>
    <subfield code="b">PDF</subfield>
    <subfield code="2">rda</subfield>
  </datafield>
  <datafield tag="490" ind1="1" ind2=" ">
    <subfield code="a">Undergraduate Topics in Computer Science,</subfield>
    <subfield code="x">1863-7310 ;</subfield>
    <subfield code="v">0</subfield>
  </datafield>
  <datafield tag="505" ind1="0" ind2=" ">
    <subfield code="a">Introduction -- Representation -- Nearest Neighbour Based Classifiers -- Bayes Classifier -- Hidden Markov Models -- Decision Trees -- Support Vector Machines -- Combination of Classifiers -- Clustering -- Summary -- An Application: Handwritten Digit Recognition.</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
    <subfield code="a">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.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2="0">
    <subfield code="a">COMPUTER SCIENCE.</subfield>
  </datafield>
  <datafield tag="650" ind1="1" ind2="4">
    <subfield code="a">COMPUTER SCIENCE.</subfield>
  </datafield>
  <datafield tag="650" ind1="2" ind2="4">
    <subfield code="a">COMPUTER SCIENCE, GENERAL.</subfield>
  </datafield>
  <datafield tag="700" ind1="1" ind2=" ">
    <subfield code="a">Devi, V. Susheela.</subfield>
    <subfield code="e">author.</subfield>
  </datafield>
  <datafield tag="710" ind1="2" ind2=" ">
    <subfield code="a">SpringerLink (Online service)</subfield>
  </datafield>
  <datafield tag="773" ind1="0" ind2=" ">
    <subfield code="t">Springer eBooks</subfield>
  </datafield>
  <datafield tag="776" ind1="0" ind2="8">
    <subfield code="i">Printed edition:</subfield>
    <subfield code="z">9780857294944</subfield>
  </datafield>
  <datafield tag="830" ind1=" " ind2="0">
    <subfield code="a">Undergraduate Topics in Computer Science,</subfield>
    <subfield code="x">1863-7310 ;</subfield>
    <subfield code="v">0</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2="0">
    <subfield code="u">http://dx.doi.org/10.1007/978-0-85729-495-1</subfield>
    <subfield code="z">Ver el texto completo en las instalaciones del CICY</subfield>
  </datafield>
  <datafield tag="912" ind1=" " ind2=" ">
    <subfield code="a">ZDB-2-SCS</subfield>
  </datafield>
  <datafield tag="942" ind1=" " ind2=" ">
    <subfield code="2">ddc</subfield>
    <subfield code="c">ER</subfield>
  </datafield>
  <datafield tag="999" ind1=" " ind2=" ">
    <subfield code="c">35978</subfield>
    <subfield code="d">35978</subfield>
  </datafield>
  <datafield tag="952" ind1=" " ind2=" ">
    <subfield code="0">0</subfield>
    <subfield code="1">0</subfield>
    <subfield code="2">ddc</subfield>
    <subfield code="4">0</subfield>
    <subfield code="7">0</subfield>
    <subfield code="8">LE</subfield>
    <subfield code="a">CICY</subfield>
    <subfield code="b">CICY</subfield>
    <subfield code="c">EL</subfield>
    <subfield code="d">2025-10-06</subfield>
    <subfield code="l">0</subfield>
    <subfield code="o">004</subfield>
    <subfield code="r">2025-10-06 08:44:44</subfield>
    <subfield code="w">2025-10-06</subfield>
    <subfield code="y">ER</subfield>
  </datafield>
</record>
