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Factorization Methods for Discrete Sequential Estimation

Factorization Methods for Discrete Sequential Estimation

Factorization Methods for Discrete Sequential Estimation
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Factorization Methods for Discrete Sequential Estimation Paperback - 2006

by Bierman, Gerald J

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Description

Mineola NY: Dover, 2006. Reprint. Paperback. As New. unabridged republication of the Academic Press 1977 edition. 256 pages. "This estimation reference text thoroughly describes matrix factorization methods successfully employed by numerical analysts, familiarizing readers with the techniques that lead to efficient, economical, reliable, and flexible estimation algorithms." ; 5 3/8 x 8 1/2
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Details

  • Title Factorization Methods for Discrete Sequential Estimation
  • Author Bierman, Gerald J
  • Binding Paperback
  • Edition Reprint
  • Condition New
  • Pages 258
  • Volumes 1
  • Language ENG
  • Publisher Dover, Mineola NY
  • Publication date 2006
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index, Table of Contents
  • Bookseller's Inventory # 52008
  • ISBN 9780486449814 / 0486449815
  • Weight 0.59 lbs (0.27 kg)
  • Dimensions 8.5 x 5.52 x 0.51 in (21.59 x 14.02 x 1.30 cm)
  • Category Mathematics
  • Library of Congress subjects Control theory, Matrices
  • Library of Congress Catalogue Number 2007280888
  • Dewey Decimal Code 519.54
  • Quantity available 1

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Reader reviews for Factorization Methods for Discrete Sequential Estimation

From the publisher

This estimation reference text thoroughly describes matrix factorization methods successfully employed by numerical analysts, familiarizing readers with the techniques that lead to efficient, economical, reliable, and flexible estimation algorithms.
Topics include a review of least squares data processing and the Kalman filter algorithm; positive definite matrices, the Cholesky decomposition, and some of their applications; Householder orthogonal transformations; sequential square root data processing; mapping effects and process noise; biases and correlated process noise; and covariance analysis of effects due to mismodeled variables and incorrect filter a priori statistics. The concluding chapters explore SRIF error analysis of effects due to mismodeled variables and incorrect filter a priori statistics as well as square root information smoothing. Geared toward advanced undergraduates and graduate students, this pragmatically oriented and detailed presentation is also a useful reference, featuring numerous helpful appendixes throughout the text.
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