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Hybrid pattern recognition

There are two basic approaches to pattern recognition: decision-theoretic and syntactic. However, in actual applications, a combination of both may be needed. One such hybrid technique consists of syntactic method coupled with stochasticity in its grammar. Randomness in the syntactic case is caused due to noise and insufficient information about characteristics of pattern classes. To absorb the effect of this randomness, the grammar must be generalized to include the probabilities of production rules.
In this paper, a preliminary discussion of issues involved with hybrid techniques, in general, and stochastic grammars, in particular, is provided. An efficient algorithm for an automatic learning of production probabilities is devised. Concepts are illustrated via examples.

Identiferoai:union.ndltd.org:auctr.edu/oai:digitalcommons.auctr.edu:dissertations-4098
Date01 May 1987
CreatorsPlacide, Eustache
PublisherDigitalCommons@Robert W. Woodruff Library, Atlanta University Center
Source SetsAtlanta University Center
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceETD Collection for AUC Robert W. Woodruff Library

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