Pattern Classifiers and Trainable Machines

  • Jack Sklansky
  • Gustav N. Wassel

Table of contents

  1. Front Matter
    Pages i-xi
  2. Jack Sklansky, Gustav N. Wassel
    Pages 1-30
  3. Jack Sklansky, Gustav N. Wassel
    Pages 31-78
  4. Jack Sklansky, Gustav N. Wassel
    Pages 79-121
  5. Jack Sklansky, Gustav N. Wassel
    Pages 122-169
  6. Jack Sklansky, Gustav N. Wassel
    Pages 170-234
  7. Jack Sklansky, Gustav N. Wassel
    Pages 235-283
  8. Jack Sklansky, Gustav N. Wassel
    Pages 284-312
  9. Back Matter
    Pages 313-335

About this book


This book is the outgrowth of both a research program and a graduate course at the University of California, Irvine (UCI) since 1966, as well as a graduate course at the California State Polytechnic University, Pomona (Cal Poly Pomona). The research program, part of the UCI Pattern Recogni­ tion Project, was concerned with the design of trainable classifiers; the graduate courses were broader in scope, including subjects such as feature selection, cluster analysis, choice of data set, and estimates of probability densities. In the interest of minimizing overlap with other books on pattern recogni­ tion or classifier theory, we have selected a few topics of special interest for this book, and treated them in some depth. Some of this material has not been previously published. The book is intended for use as a guide to the designer of pattern classifiers, or as a text in a graduate course in an engi­ neering or computer science curriculum. Although this book is directed primarily to engineers and computer scientists, it may also be of interest to psychologists, biologists, medical scientists, and social scientists.


Klassifikation Lernender Automat Mustererkennung classifikation material pattern recognition

Authors and affiliations

  • Jack Sklansky
    • 1
  • Gustav N. Wassel
    • 2
  1. 1.Department of Electrical EngineeringUniversity of California at IrvineIrvineUSA
  2. 2.Department of Electronic and Electrical EngineeringCalifornia Polytechnic State UniversitySan Luis ObispoUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York 1981
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-5840-7
  • Online ISBN 978-1-4612-5838-4
  • About this book