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Proceedings of the IEEE
Paper

State of the Art in Pattern Recognition

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Abstract

This paper reviews statistical, adaptive, and heuristic techniques used in laboratory investigations of pattern recognition problems. The discussion includes correlation methods, discriminant analysis, maximum likelihood decisions, minimax techniques, perceptron-like algoritbms feature extraction, preprocessing, clustering, and nonsupervised learning. Two-dimensional distributions are used to illustrate the properties of the various procedures. Several experimental projects, representative of prospective applications, are also described. Copyright © 1968 by The Institute of Electrical and Electronic Engineering, Inc.

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Proceedings of the IEEE

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