Titlebook: Recognition of Patterns; Using the Frequencie Peter W. Becker Book 1978Latest edition Peter W. Becker, Copenhagen 1978 Patterns.classificat

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S, a Measure of Separability,rs of Class A with the probability density function f. = f.(Ξ.) from members of Class B with the density function f. = f.(Ξ.)? Seven measures of separability were mentioned, one of which was the S-measure defined by Equation 4.1. .a and σ. are the mean and standard deviation for f.. b and σ. are the

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The Heuristic Search Procedure, That such new and better attributes may be found by an organized, economical, non-exhaustive search through a hierarchical structure is one of the interesting features of the FOBW-method. In general, such a search cannot be performed among pattern attributes used with other design methods. But when

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The Heuristic Search Procedure, the FOBW-method is used, all attributes are similar in nature, they are frequencies of occurrence of binary words, and simple relationships become possible among the frequencies, as illustrated by Equations 3.4, 3.14, and 3.24.

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General Electric Company‘s Electronics Laboratory, Syracuse, N.Y., U.S.A. The author would like to take this opportunity to express his gratitude to the Electronics Laboratory for its support and encouragement in this work. Thanks are in particular due to Dr. J.J. Suran for his continued interest a

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Problems in the Design of Pattern Recognizers,ethod is the observed frequency of occurrence of some specified binary word. The method is therefore called: The Frequency of Occurrence of Binary Words Method, or the FOBW method. The method should also be of value to related disciplines where pattern recognition concepts are used, e.g., artificial intelligence and robotology.