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System Identification: A Frequency Domain Approach [Hardcover]

Rik Pintelon (Author), Johan Schoukens (Author)
5.0 out of 5 stars  See all reviews (1 customer review)

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Book Description

January 1, 2001 0780360001 978-0780360006 1
Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction. Readers in many fields of engineering will gain knowledge about:
* Choice of experimental setup and experiment design
* Automatic characterization of disturbing noise
* Generation of a good plant model
* Detection, qualification, and quantification of nonlinear distortions
* Identification of continuous- and discrete-time models
* Improved model validation tools
and from the theoretical side about:
* System identification
* Interrelations between time- and frequency-domain approaches
* Stochastic properties of the estimators
* Stochastic analysis
System Identification: A Frequency Domain Approach is written for practicing engineers and scientists who do not want to delve into mathematical details of proofs. Also, it is written for researchers who wish to learn more about the theoretical aspects of the proofs. Several of the introductory chapters are suitable for undergraduates. Each chapter begins with an abstract and ends with exercises, and examples are given throughout.

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From the Back Cover

Electrical Engineering System Identification A Frequency Domain Approach How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction. Readers in many fields of engineering will gain knowledge about:
* Choice of experimental setup and experiment design
* Automatic characterization of disturbing noise
* Generation of a good plant model
* Detection, qualification, and quantification of nonlinear distortions
* Identification of continuous- and discrete-time models
* Improved model validation tools
and from the theoretical side about:
* System identification
* Interrelations between time- and frequency-domain approaches
* Stochastic properties of the estimators
* Stochastic analysis
System Identification: A Frequency Domain Approach is written for practicing engineers and scientists who do not want to delve into mathematical details of proofs. Also, it is written for researchers who wish to learn more about the theoretical aspects of the proofs. Several of the introductory chapters are suitable for undergraduates. Each chapter begins with an abstract and ends with exercises, and examples are given throughout.

About the Author

About the Authors Rik Pintelon and Johan Schoukens are professors of electrical engineering at the Vrije Universiteit Brussels, Brussels, Belgium. They share research interests in system identification, signal processing, and measurement techniques. They are the coauthors of a software package with a user-friendly graphical user interface called Frequency Domain System Identification Toolbox for Matlab(r), which covers the methods discussed in this book.

Product Details

  • Hardcover: 648 pages
  • Publisher: Wiley-IEEE Press; 1 edition (January 1, 2001)
  • Language: English
  • ISBN-10: 0780360001
  • ISBN-13: 978-0780360006
  • Product Dimensions: 10.2 x 7.2 x 1.5 inches
  • Shipping Weight: 2.9 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #1,535,373 in Books (See Top 100 in Books)

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1 of 8 people found the following review helpful:
5.0 out of 5 stars Highly recommended!, March 31, 2007
This review is from: System Identification: A Frequency Domain Approach (Hardcover)
This book offers an excellent introduction to system identification. All the steps in the modelling process are covered, from measurement aspects to consistency analysises of estimators.
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Inside This Book (learn more)
First Sentence:
Abstract: In this chapter a brief, intuitive introduction to the identification theory is given. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
random multisine, parametric noise model, stochastic nonlinear contributions, deterministic weighting, phase multisine, stochastic convergence rate, independent repeated experiments, real model parameters, bootstrapped total least squares, scalar orthogonal polynomials, considered model set, flight flutter data, complex model parameters, noiseless solutions, stochastic weighting, generalized total least squares, identifiable parameterization, crest factor minimization, frequency response function measurements, multisine excitation, odd multisine, true plant model, antialias protection, plant model errors, small model errors
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Identification of Semilinear Models, Models of Linear Time-Invariant Systems, Measurements of Frequency Response Functions, Estimator Using, Proof See Appendix, Some Linear Algebra Fundamentals, Vrije Universiteit Brussel, Consistency Condition, Applying the Gram-Schmidt, Consider Examples, Method Prediction, Monte Carlo, Properties of Least Squares Estimators, Properties Sample Correlation, Repeat Exercise
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