Continuously discrete estimation of stochastic processes for observations with memory under anomalous noise: Synthesis

Abstract

An mean square optimal unbiased filter-interpolator-extrapolator for continuous-time processes is synthesized on the basis of the set of realizations of continuous and discrete time processes. It is supposed that these processes depend not only on the current values of an unobserved process, but on an arbitrary number of its preceding values as well; the extrapolation is performed at an arbitrary number of future instants, and anomalous noise occurs in discrete observations.

Original language	English
Pages (from-to)	335-346
Number of pages	12
Journal	Journal of Computer and Systems Sciences International
Volume	39
Issue number	3
Publication status	Published - 2000

ASJC Scopus subject areas

Artificial Intelligence
Computational Theory and Mathematics
Human-Computer Interaction
Control and Systems Engineering
Theoretical Computer Science

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title = "Continuously discrete estimation of stochastic processes for observations with memory under anomalous noise: Synthesis",

abstract = "An mean square optimal unbiased filter-interpolator-extrapolator for continuous-time processes is synthesized on the basis of the set of realizations of continuous and discrete time processes. It is supposed that these processes depend not only on the current values of an unobserved process, but on an arbitrary number of its preceding values as well; the extrapolation is performed at an arbitrary number of future instants, and anomalous noise occurs in discrete observations.",

author = "Demin, {N. S.} and Rozhkova, {S. V.}",

year = "2000",

language = "English",

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pages = "335--346",

journal = "Journal of Computer and Systems Sciences International",

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AB - An mean square optimal unbiased filter-interpolator-extrapolator for continuous-time processes is synthesized on the basis of the set of realizations of continuous and discrete time processes. It is supposed that these processes depend not only on the current values of an unobserved process, but on an arbitrary number of its preceding values as well; the extrapolation is performed at an arbitrary number of future instants, and anomalous noise occurs in discrete observations.

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