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Advances in Nonparametric Techniques of Statistical Pattern Classification

  • Conference paper
Pattern Recognition Theory and Applications

Part of the book series: NATO Advanced Study Institutes Series ((ASIC,volume 81))

Abstract

This paper is concerned with nonparametric statistical pattern recognition and focuses on some theoretical advances that have taken place since the previous NATO Advanced Study Institute on Pattern Recognition Theory and Applications held in Bandol, France, in 1975, [1]. In an article of this size, it is not feasible to cover the field exhaustively. Therefore, the aim of our selective discussion of topics is merely to give a limited perspective on how statistical theories of pattern classification have evolved during the last six years.

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Author information

Authors and Affiliations

  1. Philips Research Laboratory, Brussels, Belgium

    Pierre A. Devijver

Authors
  1. Pierre A. Devijver
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Editor information

Editors and Affiliations

  1. Science and Engineering Research Council, Rutherford and Appleton Laboratories, Chilton, Didcot, England

    Josef Kittler

  2. Oxford, UK

    Josef Kittler

  3. Purdue University, West Lafayette, Indiana, USA

    King Sun Fu

  4. Ecole Nationale Superieure des Telecommunications, Paris, France

    Louis-François Pau

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© 1982 D. Reidel Publishing Company

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Devijver, P.A. (1982). Advances in Nonparametric Techniques of Statistical Pattern Classification. In: Kittler, J., Fu, K.S., Pau, LF. (eds) Pattern Recognition Theory and Applications. NATO Advanced Study Institutes Series, vol 81. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-7772-3_1

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  • DOI: https://doi.org/10.1007/978-94-009-7772-3_1

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-009-7774-7

  • Online ISBN: 978-94-009-7772-3

  • eBook Packages: Springer Book Archive

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