A note on sequential decision approach to pattern recognition and machine learning*

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A pattern recognition system has been formulated with the framework of sequential decision theory. Recognition of multiple pattern class with features properly ordered is considered. The system can switch from supervised learning to unsupervised learning to continuously improve the performance. Application of the work to computer recognition of handprinted and handwritten English characters is examined in detail.

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*

Part of the work reported in this paper was done for a Ph.D. dissertation submitted to Purdue University, and was supported by David Ross Grant PRF 3373.

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