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Article

Title: Least squares in identification theory (English)
Author: Strejc, Vladimír
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 13
Issue: 2
Year: 1977
Pages: (83)-105
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Category: math
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MSC: 93B30
MSC: 93E10
MSC: 93E25
idZBL: Zbl 0354.93061
idMR: MR0504266
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Date available: 2009-09-24T16:55:26Z
Last updated: 2012-06-05
Stable URL: http://hdl.handle.net/10338.dmlcz/124284
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Reference: [1] T. W. Anderson: An Introduction to Multivariate Statistical Analysis.John Wiley & Sons, Inc., New York, Chapman and Hall, Ltd., 1958. Zbl 0083.14601, MR 0091588
Reference: [2] Д. K. Фаддеев B. H. Фаддеева: Вычислительные методы линейной алгебры.Физматгиз, Mocквa 1960. Zbl 1225.94001
Reference: [3] M. G. Kendall, A. Stuart: The Advanced Theory of Statistics. Vol. 2.Griffin, London. 1961.
Reference: [4] A. S. Householder: The Theory of Matrices in Numerical Analysis.Waltham, Mas., Blaisdell. 1964. Zbl 0161.12101, MR 0175290
Reference: [5] A. Bjorck: Solving Linear Least Squares Problems by Gram-Schmidt Orthogonalization.BIT 7, 1967, 1-21. MR 0214275
Reference: [6] D. W. Clarke: Generalized Least Squares Estimation of the Parameters of a Dynamic Model.Preprints, First IFAC Symposium on Identification, Prague, 1967.
Reference: [7] P. Eykhoff: Process Parameter and State Estimation.Survey Paper, First IFAC Symposium on Identification, Prague, 1967.
Reference: [8] D. Q. Mayne: A Method for Estimating Discrete Time Transfer Functions.In: Advances in Computer Control, Second UKAC Control Convention, The Univ. of Bristol, 1967.
Reference: [9] K. Y. Wong, E. Polak: Identification of Linear Discrete Time System Using the Instrumental Variable Method.IEEE Trans, on Automatic Control, AC-12, 1967, 707-718.
Reference: [10] V. Panuska: A Stochastic Approximation Method for Identification of Linear Systems using Adaptive Filtering.In preprints JACC, The Univ. of Michigan, 1968, 1014-1021.
Reference: [11] R. Deutsch: Estimation Theory.Prentice-Hall, Inc., Englewood Cliffs, N. J., 1969. MR 0192572
Reference: [12] R. Hastings-James, M. W. Sage: Recursive Generalized Least Squares Procedure for On-Line Identification of Process Parameters.Proc. of the IEE 116, 12, 1969, 2057-2062.
Reference: [13] K. Smuk, V. Peterka: On-line Estimation of Dynamic Model Parameters from Input-Output Data.4th IFAC Congress, Warsaw, 1969.
Reference: [14] V. Peterka, A. Halousková: Tally Estimate of Astrom Model for Stochastic Systems.Second IFAC Symposium on Identification and Process Parameter Estimation, Prague, 1970.
Reference: [15] P. C. Young: An Extension to the Instrumental Variable Method for Identification of a Noisy Dynamic Process.Dep. Eng., Univ. Cambridge, England, Techn. Note CN/70/1, 1970.
Reference: [16] P. C. Young, R. Hastings-James: Identification and Control of Discrete Dynamic Systems Subject to Disturbances with Rational Spectral Density.Proc. 9th IEEE Symp., Adaptive Processes, 1970.
Reference: [17] P. G. Kaminski A. E. Bryson Ir. S. F. Schmidt: Discrete Square Root Filtering. A Survey of Current Techniques.IEEE Trans, on Automatic Control AC-16, 1971, 727-735.
Reference: [18] L. Ljung T. Soderstrom, I. Gustavsson: Counterexamples to General Convergence of a Commonly Used Recursive Identification Method.IEEE Trans. on Automatic Control, AC-20, 1975, 643-652. MR 0401297
Reference: [19] V. Peterka: A Square Root Filter for Real Time Multivariate Regression.Kybernetika 11, 1975, 53-67. Zbl 0314.62028, MR 0403769
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