Elsevier

Information Sciences

Volume 6, 1973, Pages 301-311
Information Sciences

Detection and prediction of a stochastic process having multiple hypotheses☆

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Abstract

A system is proposed which combines hypothesis testing and prediction to estimate the future value of a stochastic process whose statistics are known only to belong to some finite set of possible hypotheses. Bayes optimization of the individual components is performed, and system performance is discussed for a modified version of the usual mean-squared error predictor cost functions. An example is given illustrating various features of the system's performance for a specific choice of input hypotheses.

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☆

This work was supported by the Joint Electronics Program under contract DAAB-07-67-C-0199.

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