Generalized moving extrapolation of stochastic processes based on the totality of continuous and discrete observations with memory

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8 Citations (Scopus)

Abstract

The problem of simultaneous moving extrapolation (forecast, prediction) is considered or stochastic processes with continuous time at an arbitrary number of future instants based on the totality of realizations of processes with continuous and discrete time, which depend on both the current and the past values of a nonobserved process.

Original languageEnglish
Pages (from-to)523-535
Number of pages13
JournalJournal of Computer and Systems Sciences International
Volume39
Issue number4
Publication statusPublished - 2000

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Discrete Observations
Random processes
Extrapolation
Stochastic Processes
Data storage equipment
Instant
Forecast
Continuous Time
Discrete-time
Prediction
Arbitrary

ASJC Scopus subject areas

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

Cite this

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title = "Generalized moving extrapolation of stochastic processes based on the totality of continuous and discrete observations with memory",
abstract = "The problem of simultaneous moving extrapolation (forecast, prediction) is considered or stochastic processes with continuous time at an arbitrary number of future instants based on the totality of realizations of processes with continuous and discrete time, which depend on both the current and the past values of a nonobserved process.",
author = "Demin, {N. S.} and Rozhkova, {O. V.} and Rozhkova, {S. V.}",
year = "2000",
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journal = "Journal of Computer and Systems Sciences International",
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AU - Rozhkova, O. V.

AU - Rozhkova, S. V.

PY - 2000

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AB - The problem of simultaneous moving extrapolation (forecast, prediction) is considered or stochastic processes with continuous time at an arbitrary number of future instants based on the totality of realizations of processes with continuous and discrete time, which depend on both the current and the past values of a nonobserved process.

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VL - 39

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JO - Journal of Computer and Systems Sciences International

JF - Journal of Computer and Systems Sciences International

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