Smoothing Estimation of Stochastic Processes. Part II. Two Filter Formulae.

Abstract

In this article these two-filter results and some new ones are derived in a simple way in a very general setting (for arbitrary nonstationary processes). It turns out however that only if a wide-sense (i.e. second order) Markovian assumption is added can one of the filters be viewed as a backwards filter. The remainder of the paper is organized as follows. Section 2 recalls some smoothing formulae that apply to both continuous and discrete observations. Section 3 discusses two types of two-filter-like formulae for general nonstationary processes. In Section 4 one of the filters is shown to be a backwards least squares estimate provided a wide sense Markovian assumption is satisfied. Section 5 contains a derivation of some backwards filters. In Section 6 some additional two-filter-like formulae are given. The final section is a conlusion.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1980
Accession Number
ADA093634

Entities

People

  • V. Solo

Organizations

  • University of Wisconsin–Madison

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Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Control Systems Engineering
  • Covariance
  • Data Science
  • Engineering
  • Equations
  • Hilbert Space
  • Information Science
  • Mathematical Analysis
  • Mathematics
  • Measurement
  • Order Statistics
  • Random Variables
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • United States

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  • Mathematics

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  • Mathematical Modeling and Probability Theory.
  • Statistical inference.