Detection and prediction of a stochastic process having multiple hypotheses

D. W. Kelsey, A. H. Haddad*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


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)
Pages (from-to)301-311
Number of pages11
JournalInformation Sciences
Issue numberC
StatePublished - 1973

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence


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