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Note on a Class of Statistical Recognition Functions

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1 Author(s)

Statistical recognition procedures can be derived from the functional form of underlying probability distributions. Successive approximation to the probability function leads to a class of recognition procedures. In this note we give a hierarchical method of designing recognition functions which satisfy both the least-square error property and a minimum decision error rate property, although our discussions are restricted to a binary measurement space and its dichotomous classification.

Published in:

Computers, IEEE Transactions on  (Volume:C-18 ,  Issue: 1 )

Date of Publication:

Jan. 1969

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