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• W2129058435 abstract "This paper is concerned with the adaptive prediction for stochastic processes with abruptly changing parameters modelled as a finite-state Markov chain. The Markov transition matrix is assumed to be known. For the coloured noise disturbance case, it is shown that the optimal prediction algorithm requires a bank of elemental predictors running in parallel with its number growing exponentially with time. If the noise disturbance is white, it is found that the number of the elemental predictors required increases exponentially with the prediction ahead step instead of time. A suboptimal predictor is proposed with substantial reduced storage and computational requirements. Simulation examples show the good performance of the proposed algorithms." @default.
• W2129058435 created "2016-06-24" @default.
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• W2129058435 date "1988-04-01" @default.
• W2129058435 modified "2023-10-01" @default.
• W2129058435 title "Adaptive prediction for stochastic processes with markov jump parameters" @default.
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• W2129058435 doi "https://doi.org/10.1002/for.3980070204" @default.
• W2129058435 hasPublicationYear "1988" @default.
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