000 06951nam a2201225 i 4500
001 6198969
003 IEEE
005 20230927112354.0
006 m o d
007 cr |n|||||||||
008 151221s2012 njua ob 001 eng d
020 _a9781118287422
_qebook
020 _z9780470640371
_qcloth
020 _z0470640375
_qcloth
020 _z1118287428
_qelectronic
024 8 _a9786613651617
035 _a(CaBNVSL)mat06198969
035 _a(IDAMS)0b00006481812a5e
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
100 1 _aPintelon, R.,
_q(Rik)
_eauthor.
245 1 0 _aSystem identification :
_ba frequency domain approach /
_cRik Pintelon, Johan Schoukens.
250 _a2nd ed.
264 1 _aHoboken, N.J. :
_bWiley ;
_aPiscataway, NJ :
_bIEEE Press,
264 2 _a[Piscataqay, New Jersey] :
_bIEEE Xplore,
_c[2012]
300 _a1 PDF (xliv, 743 pages) :
_billustrations.
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
500 _a"MATLAB examples"--T.p.
504 _aIncludes bibliographical references and indexes.
505 0 _aPreface to the First Edition -- -- Preface to the Second Edition -- -- Acknowledgments -- -- List of Operators and Notational Conventions -- List of Symbols -- List of Abbreviations -- Chapter 1 An Introduction to Identification -- Chapter 2 Measurement of Frequency Response Functions - Standard Solutions -- Chapter 3 Frequency Response Function Measurements in the Presence of Nonlinear Distortions -- Chapter 4 Detection, Quantification, and Qualification of Nonlinear Distortions in FRF Measurements -- Chapter 5 Design of Excitation Signals -- Chapter 6 Models of Linear Time-Invariant Systems -- Chapter 7 Measurement of Frequency Response Functions - The Local Polynomial Approach -- Chapter 8 An Intuitive Introduction to Frequency Domain Identification -- Chapter 9 Estimation with Know Noise Model -- Chapter 10 Estimation with Unknown Noise Model - Standard Solutions -- Chapter 11 Model Selection and Validation -- Chapter 12 Estimation with Unknown Noise Model - The Local Polynomial Approach -- Chapter 13 Basic Choices in System Identification -- Chapter 14 Guidelines for the User -- Chapter 15 Some Linear Algebra Fundamentals -- Chapter 16 Some Probability and Stochastic Convergence Fundamentals -- Chapter 17 Properties of Least Squares Estimators with Deterministic Weighting -- Chapter 18 Properties of Least Squares Estimators with Stochastic Weighting -- Chapter 19 Identification of Semilinear Models -- Chapter 20 Identification of Invariants of (Over) Parameterized Models -- References -- Subject Index -- Author Index -- About the Authors
506 1 _aRestricted to subscribers or individual electronic text purchasers.
520 _aSystem 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.Focusing 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.Readers of this Second Editon will benefit from:. MATLAB software support for identifying multivariable systems that is freely available at the website http://booksupport.wiley.com. State-of-the-art system identification methods for both time and frequency domain data. New chapters on non-parametric and parametric transfer function modeling using (non-)period excitations. Numerous examples and figures that facilitate the learning process. A simple writing style that allows the reader to learn more about the theo??retical aspects of the proofs and algorithmsUnlike 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.
530 _aAlso available in print.
538 _aMode of access: World Wide Web
588 _aDescription based on PDF viewed 12/21/2015.
650 0 _aSystem identification.
655 0 _aElectronic books.
695 _aApproximation methods
695 _aBoundary conditions
695 _aBroadband communication
695 _aConvergence
695 _aCorrelation
695 _aCost function
695 _aCovariance matrix
695 _aCurrent measurement
695 _aData models
695 _aDiscrete Fourier transforms
695 _aDistortion measurement
695 _aEigenvalues and eigenfunctions
695 _aElectrical resistance measurement
695 _aEquations
695 _aEstimation
695 _aFrequency domain analysis
695 _aFrequency estimation
695 _aFrequency response
695 _aGaussian noise
695 _aGuidelines
695 _aHarmonic analysis
695 _aIndexes
695 _aLaplace equations
695 _aLeast squares approximation
695 _aMarkov processes
695 _aMathematical model
695 _aMatrix decomposition
695 _aMaximum likelihood estimation
695 _aMeasurement uncertainty
695 _aNoise
695 _aNoise measurement
695 _aNonlinear distortion
695 _aNonlinear systems
695 _aNull space
695 _aNumerical models
695 _aPhase measurement
695 _aPoles and zeros
695 _aPolynomials
695 _aProbability density function
695 _aRandom variables
695 _aResistors
695 _aSensitivity
695 _aSignal to noise ratio
695 _aSingular value decomposition
695 _aSpectral analysis
695 _aStochastic processes
695 _aSymmetric matrices
695 _aSystem identification
695 _aSystematics
695 _aTime domain analysis
695 _aTime factors
695 _aTime frequency analysis
695 _aTime measurement
695 _aTransfer functions
695 _aTransient analysis
695 _aUncertainty
695 _aVectors
695 _aVoltage measurement
695 _aWeight measurement
695 _aActuators
700 1 _aSchoukens, J.
_q(Johan)
710 2 _aIEEE Xplore (Online Service),
_edistributor.
710 2 _aWiley InterScience (Online service),
_epublisher.
776 0 8 _iPrint version:
_z9780470640371
856 4 2 _3Abstract with links to resource
_uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6198969
999 _c40497
_d40497