Pattern Recognition in Chemistry

  • Kurt Varmuza

Part of the Lecture Notes in Chemistry book series (LNC, volume 21)

Table of contents

  1. Front Matter
    Pages N1-XI
  2. Introduction to Some Pattern Recognition Methods

    1. Front Matter
      Pages 1-1
    2. Kurt Varmuza
      Pages 2-17
    3. Kurt Varmuza
      Pages 18-61
    4. Kurt Varmuza
      Pages 72-77
    5. Kurt Varmuza
      Pages 78-87
    6. Kurt Varmuza
      Pages 88-91
    7. Kurt Varmuza
      Pages 92-96
    8. Kurt Varmuza
      Pages 97-101
    9. Kurt Varmuza
      Pages 102-105
    10. Kurt Varmuza
      Pages 106-117
    11. Kurt Varmuza
      Pages 118-140
  3. Application of Pattern Recognition Methods in Chemistry

    1. Front Matter
      Pages 141-141
    2. Kurt Varmuza
      Pages 145-165
    3. Kurt Varmuza
      Pages 166-168
    4. Kurt Varmuza
      Pages 169-170
    5. Kurt Varmuza
      Pages 184-184
    6. Kurt Varmuza
      Pages 185-187
    7. Kurt Varmuza
      Pages 188-188
  4. Appendix

    1. Front Matter
      Pages 189-189
    2. Kurt Varmuza
      Pages 190-211
  5. Back Matter
    Pages 212-221

About this book


Analytical chemistry of the recent years is strongly influenced by automation. Data acquisition from analytica~ instruments - and some­ times also controlling of instruments - by a computer are principally solved since many years. Availability of microcomputers made these tasks also feasible from the economic point of view. Besides these basic applications of computers in chemical measurements scientists developed computer programs for solving more sophisticated problems for which some kind of "intelligence" is usually supposed to be necessary. Harm­ less numerical experiments on this topic led to passionate discussions about the theme "which jobs cannot be done by a computer but only by human brain ?~. If this question is useful at all it should not be ans­ wered a priori. Application of computers in chemistry is a matter of utility, sometimes it is a social problem, but it is never a question of piety for the human brain. Automated instruments and the necessity to work on complex pro­ blems enhanced the development of automatic methods for the reduction and interpretation of large data sets. Numerous methods from mathematics, statistics, information theory, and computer science have been exten­ sively investigated for the elucidation of chemical information; a new discipline "chemometrics" has been established. Three different approaches have been used for computer-assisted interpretations of chemical data. 1. Heuristic methods try to formu­ late computer programs working in a similar way as a chemist would solve the problem. 2.


Chemie Mustererkennung classification clustering pattern pattern recognition spectroscopy

Authors and affiliations

  • Kurt Varmuza
    • 1
  1. 1.Institut für Allgemeine ChemieTechnischen Universität WienWienAustria

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 1980
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-10273-1
  • Online ISBN 978-3-642-93155-0
  • Series Print ISSN 0342-4901
  • Series Online ISSN 2192-6603
  • Buy this book on publisher's site