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1. Introduction 2. Review of Least Squares Data Processing and the Kalman Filter Algorithm 3. Positive Definite Matrices, the Cholesky Decomposition, and Some Applications 4. Householder Orthogonal Transformations 5. Sequential Square Root Data Processing 6. Inclusion of Mapping Effects and Process Noise 7. Treatment of Biases and Correlated Process Noise 8. Covariance Analysis of Effects Due to Mismodeled Variables and Incorrect Filter a Priori Statistics 9. SRIF Error Analysis of Effects Due to Mismodeled Variables and Incorrect Filter a Prior Statistics 10. Square Root Information Smoothing Bibliography Index
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. Geared toward advanced undergraduates and graduate students, this pragmatically oriented presentation is also a useful reference, featuring numerous appendixes. 1977 edition.
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Da: HPB-Red, Dallas, TX, U.S.A.
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Paperback or Softback. Condizione: New. Factorization Methods for Discrete Sequential Estimation. Book. Codice articolo BBS-9780486449814
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Da: Chequamegon Books, Washburn, WI, U.S.A.
Paperback. Condizione: As New. Reprint. 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 ". Codice articolo 52008
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. 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. Geared toward advanced undergraduates and graduate students, this text describes matrix factorization methods employed by numerical analysts, featuring techniques that lead to efficient, economical, reliable, and flexible estimation algorithms. 1977 edition. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780486449814
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