A Scattering Theory Framework for Fast Least-Squares Algorithms,

Abstract

In scattering theory the Riccati equation arises in a natural family of equations evolving forwards as well as backwards in time. The authors show how this framework allows an interesting derivation of the fast Chandrasekhar-type equations for linear least-squares filtering of processes generated by a time-invariant, finite-dimensional linear system driven by white noise. The processes are not required to be stationary. The same ideas can be used to obtain Levinson- and Cholesky-type differential equations for the impulse responses of the whitening filter and the innovations representation of such processes. The scattering framework brings out clearly both the significance of the time-invariance of the parameters of the underlying finite-dimensional system and of the associated family of nonstationary processes. For stationary processes, it also becomes clear that the assumption of finite-dimensionality is unnecessary, but the proper extension of the nonstationary class of processes raises some interesting questions.

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1975
Accession Number
ADA029790

Entities

People

  • L. Ljung
  • Thomas Kailath

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Data Science
  • Differential Equations
  • Equations
  • Information Science
  • Linear Systems
  • Multivariate Analysis
  • Partial Differential Equations
  • Riccati Equation
  • Scattering
  • Stationary
  • Stationary Processes
  • White Noise

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.