{"product_id":"system-identification-isbn-9780470640371","title":"System Identification","description":"\u003cp\u003eSystem identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering.\u003c\/p\u003e \u003cp\u003eFocusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identification process, points out the possible pitfalls to the reader, and illustrates the powerful tools that are available.\u003c\/p\u003e \u003cp\u003eReaders of this Second Editon will benefit from:\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMATLAB software support for identifying multivariable systems that is freely available at the website http:\/\/booksupport.wiley.com\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eState-of-the-art system identification methods for both time and frequency domain data\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eNew chapters on non-parametric and parametric transfer function modeling using (non-)period excitations\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eNumerous examples and figures that facilitate the learning process\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eA simple writing style that allows the reader to learn more about the theo??retical aspects of the proofs and algorithms\u003c\/p\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eUnlike other books in this field, System Identification, Second Edition is ideal for practicing engineers, scientists, researchers, and both master's and PhD students in electrical, mechanical, civil, and chemical engineering.\u003c\/p\u003e  \u003cp\u003ePreface to the First Edition\u003cbr\u003e \u003cbr\u003e Preface to the Second Edition\u003cbr\u003e \u003cbr\u003e Acknowledgments\u003cbr\u003e \u003cbr\u003e List of Operators and Notational Conventions\u003c\/p\u003e \u003cp\u003eList of Symbols\u003c\/p\u003e \u003cp\u003eList of Abbreviations\u003c\/p\u003e \u003cp\u003eChapter 1 An Introduction to Identification\u003c\/p\u003e \u003cp\u003eChapter 2 Measurement of Frequency Response Functions – Standard Solutions\u003c\/p\u003e \u003cp\u003eChapter 3 Frequency Response Function Measurements in the Presence of Nonlinear Distortions\u003c\/p\u003e \u003cp\u003eChapter 4 Detection, Quantification, and Qualification of Nonlinear Distortions in FRF Measurements\u003c\/p\u003e \u003cp\u003eChapter 5 Design of Excitation Signals\u003c\/p\u003e \u003cp\u003eChapter 6 Models of Linear Time-Invariant Systems\u003c\/p\u003e \u003cp\u003eChapter 7 Measurement of Frequency Response Functions – The Local Polynomial Approach\u003c\/p\u003e \u003cp\u003eChapter 8 An Intuitive Introduction to Frequency Domain Identification\u003c\/p\u003e \u003cp\u003eChapter 9 Estimation with Know Noise Model\u003c\/p\u003e \u003cp\u003eChapter 10 Estimation with Unknown Noise Model – Standard Solutions\u003c\/p\u003e \u003cp\u003eChapter 11 Model Selection and Validation\u003c\/p\u003e \u003cp\u003eChapter 12 Estimation with Unknown Noise Model – The Local Polynomial Approach\u003c\/p\u003e \u003cp\u003eChapter 13 Basic Choices in System Identification\u003c\/p\u003e \u003cp\u003eChapter 14 Guidelines for the User\u003c\/p\u003e \u003cp\u003eChapter 15 Some Linear Algebra Fundamentals\u003c\/p\u003e \u003cp\u003eChapter 16 Some Probability and Stochastic Convergence Fundamentals\u003c\/p\u003e \u003cp\u003eChapter 17 Properties of Least Squares Estimators with Deterministic Weighting\u003c\/p\u003e \u003cp\u003eChapter 18 Properties of Least Squares Estimators with Stochastic Weighting\u003c\/p\u003e \u003cp\u003eChapter 19 Identification of Semilinear Models\u003c\/p\u003e \u003cp\u003eChapter 20 Identification of Invariants of (Over) Parameterized Models\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003eSubject Index\u003c\/p\u003e \u003cp\u003eAuthor Index\u003c\/p\u003e \u003cp\u003eAbout the Authors\u003c\/p\u003e \u003cp\u003e\u003cb\u003eRIK PINTELON, PhD,\u003c\/b\u003e serves as a full-time professor at the Vrije Universiteit Brussel in the ELEC Department. He has been a Fellow of IEEE since 1998 and is the recipient of the 2012 IEEE Joseph F. Keithley Award in Instrumentation and Measurement (IEEE Technical Field Award).\u003c\/p\u003e \u003cp\u003e\u003cb\u003eJOHAN SCHOUKENS, PhD,\u003c\/b\u003e serves as a full-time professor in the ELEC Department at the Vrije Universiteit Brussel. He has been a Fellow of IEEE since 1997 and was the recipient of the 2003 IEEE Instrumentation and Measurement Society Distinguished Service Award.\u003c\/p\u003e \u003cp\u003eSystem identification is a general term used to describe mathematical tools and algorithms that build dynamical models from measured data. Used for prediction, control, physical interpretation, and the designing of any electrical systems, they are vital in the fields of electrical, mechanical, civil, and chemical engineering.\u003c\/p\u003e \u003cp\u003eFocusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach. It high??lights many of the important steps in the identification process, points out the possible pitfalls to the reader, and illustrates the powerful tools that are available.\u003c\/p\u003e \u003cp\u003eReaders of this Second Editon will benefit from:\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMATLAB software support for identifying multivariable systems that is freely available at the website http:\/\/booksupport.wiley.com\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eState-of-the-art system identification methods for both time and frequency domain data\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eNew chapters on non-parametric and parametric transfer function modeling using (non-)period excitations\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eNumerous examples and figures that facilitate the learning process\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eA simple writing style that allows the reader to learn more about the theo??retical aspects of the proofs and algorithms\u003c\/p\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eUnlike other books in this field, System Identification, Second Edition is ideal for practicing engineers, scientists, researchers, and both master's and PhD students in electrical, mechanical, civil, and chemical engineering.\u003c\/p\u003e","brand":"Wiley-IEEE Press","offers":[{"title":"Default Title","offer_id":47990124445925,"sku":"NP9780470640371","price":177.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470640371.jpg?v=1761786607","url":"https:\/\/k12savings.com\/products\/system-identification-isbn-9780470640371","provider":"K12savings","version":"1.0","type":"link"}