Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling

Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling
Author: Sabine van Huffel
Publisher: SIAM
Total Pages: 404
Release: 1997-01-01
Genre: Mathematics
ISBN: 9780898713930

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An overview of the computational issues; statistical, numerical, and algebraic properties, and new generalizations and applications of advances on TLS and EIV models. Experts from several disciplines prepared overview papers which were presented at the conference and are included in this book.

The Total Least Squares Problem

The Total Least Squares Problem
Author: Sabine Van Huffel
Publisher: SIAM
Total Pages: 302
Release: 1991-01-01
Genre: Mathematics
ISBN: 0898712750

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This is the first book devoted entirely to total least squares. The authors give a unified presentation of the TLS problem. A description of its basic principles are given, the various algebraic, statistical and sensitivity properties of the problem are discussed, and generalizations are presented. Applications are surveyed to facilitate uses in an even wider range of applications. Whenever possible, comparison is made with the well-known least squares methods. A basic knowledge of numerical linear algebra, matrix computations, and some notion of elementary statistics is required of the reader; however, some background material is included to make the book reasonably self-contained.

Proceedings

Proceedings
Author:
Publisher:
Total Pages: 632
Release: 1993
Genre: Electronic data processing
ISBN:

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System Identification

System Identification
Author: Tien C. Hsia
Publisher: Free Press
Total Pages: 200
Release: 1977
Genre: Science
ISBN:

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Model Fitting in Frequency Domain Imposing Stability of the Model

Model Fitting in Frequency Domain Imposing Stability of the Model
Author: László Balogh
Publisher: ASP / VUBPRESS / UPA
Total Pages: 203
Release: 2010-09
Genre: Signal processing
ISBN: 9054876484

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After presenting a new mathematical proof, this study describes how system identification--a powerful technique for constructing accurate models of complex systems--can be used to evaluate noisy measurements. The discussion goes on to show how noisy data can be manipulated by researchers working on projects in physical interpretation, simulation, prediction, estimation, and control.