A unified approach to optimal feature selection

  • Authors:

  • Salvatore D Morgera

  • Affiliations:

  • Concordia University, Dept. of Elect. Engin. H915-13, 1455 de Maisonneuve Blvd. West, Montréal, H3G 1M8 Québec, Canada

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 1983

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Abstract

The optimum finite set of linear observables for discriminating two Gaussian stochastic processes is derived using classical methods and distribution function theory. The results offer a new, accurate information-theoretic strategy and are superior to well-known conventional methods using statistical distance measures.