‘Unobserved’ Monte Carlo Methods for Adaptive Algorithms

Victor Solo ()
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Victor Solo: University of New South Wales

Chapter Chapter 18 in Modeling Uncertainty, 2002, pp 373-382 from Springer

Abstract: Abstract Many Signal Processing and Control problems are complicated by the presence of unobserved variables. Even in linear settings this can cause problems in constructing adaptive parameter estimators. In previous work the author investigated the possibility of developing an on-line version of so-called Markov Chain Monte Carlo methods for solving these kinds of problems. In this article we present a new and simpler approach to the same group of problems based on direct simulation of unobserved variables.

Keywords: Markov Chain; Monte Carlo; Adaptive Algorithm (search for similar items in EconPapers)
Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-0-306-48102-4_18

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DOI: 10.1007/0-306-48102-2_18

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