000			02736nam a22003858i 4500
001			CR9780511618888
003			UkCbUP
005			20200124160330.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			090915s2007||||enk o ||1 0|eng|d
020			_a9780511618888 (ebook)
020			_z9780521875127 (hardback)
020			_z9781107405028 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA297 _b.V397 2007
082	0	4	_a003.1 _222
100	1		_aVerhaegen, M. _q(Michel), _eauthor.
245	1	0	_aFiltering and system identification : _ba least squares approach / _cMichel Verhaegen, Vincent Verdult.
246	3		_aFiltering & System Identification
264		1	_aCambridge : _bCambridge University Press, _c2007.
300			_a1 online resource (xv, 405 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aLinear algebra -- Discrete-time signals and systems -- Random variables and signals -- Kalman filtering -- Estimation of spectra and frequency-response functions -- Output-error parametric model estimation -- Prediction-error parametric model estimation -- Subspace model identification -- The system-identification cycle.
520			_aFiltering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127.
650		0	_aFilters (Mathematics)
650		0	_aSystem identification.
650		0	_aLeast squares.
700	1		_aVerdult, Vincent, _eauthor.
776	0	8	_iPrint version: _z9780521875127
856	4	0	_uhttps://doi.org/10.1017/CBO9780511618888
999			_c522495 _d522493