Detection and prediction of a stochastic process having multiple hypotheses

D. W. Kelsey, Abraham Herzl Haddad

Research output: Contribution to journalConference articlepeer-review


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.

Original languageEnglish (US)
Article number4044823
Pages (from-to)552-556
Number of pages5
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1971
Event1971 IEEE Conference on Decision and Control, CDC 1971 - Including the 10th Symposium on Adaptive Process - Miami Beach, United States
Duration: Dec 15 1971Dec 17 1971

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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