000			03553nam a2200361Ii 4500
001			9781315222509
008			180611s2014 fluab ob 001 0 eng d
020			_a9781315222509 _q(e-book : PDF)
035			_a(OCoLC)908635288
050		4	_aQA402
072		7	_aTEC _x007000 _2bisacsh
072		7	_aTEC _x009000 _2bisacsh
072		7	_aTHRB _2bicscc
082	0	4	_a003.1 _223
100	1		_aTangirala, Arun K., _d1974- _eauthor. _920041
245	1	0	_aPrinciples of system identification : _btheory and practice / _cby Arun K. Tangirala.
250			_aFirst edition.
264		1	_aBoca Raton, FL : _bCRC Press, an imprint of Taylor and Francis, _c2014.
300			_a1 online resource (908 pages) : _b219 illustrations
505	0		_apart Part I: Introduction to Identification and Models for Linear Deterministic Systems -- chapter 1 Introduction -- chapter 2 A Journey into Identification -- chapter 3 Mathematical Descriptions of Processes: Models -- chapter 4 Models for Discrete-Time LTI Systems -- chapter 5 Transform-Domain Models for Linear TIme-Invariant Systems -- chapter 6 Sampling and Discretization -- part Part II: Models for Random Processes -- chapter 7 Random Processes -- chapter 8 Time-Domain Analysis: Correlation Functions -- chapter 9 Models for Linear Stationary Processes -- chapter 10 Fourier Analysis and Spectral Analysis of Deterministic Signals -- chapter 11 Spectral Representations of Random Processes -- part Part III: Estimation Methods -- chapter 12 Introduction to Estimation -- chapter 13 Goodness of Estimators -- chapter 14 Estimation Methods: Part I -- chapter 15 Estimation Methods: Part II -- chapter 16 Estimation of Signal Properties -- part Part IV: Identification of Dynamic Models - Concepts and Principles -- chapter 17 Non-Parametric and Parametric Models for Identification -- chapter 18 Predictions -- chapter 19 Identification of Parametric Time-Series Models -- chapter 20 Identification of Non-Parametric Input-Output Models -- chapter 21 Identification of Parametric Input-Output Models -- chapter 22 Statistical and Practical Elements of Model Building -- chapter 23 Identification of State-Space Models -- chapter 24 Case Studies -- part Part V: Advanced Concepts -- chapter 25 Advanced Topics in SISO Identification -- chapter 26 Linear Multivariable Identification.
520	3		_aMaster Techniques and Successfully Build Models Using a Single Resource Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book focuses on system identification with an emphasis on practice, and concentrates most specifically on discrete-time linear system identification.
650		7	_aTECHNOLOGY & ENGINEERING / Engineering (General). _2bisacsh _920042
650		0	_aLinear systems. _916164
650		0	_aLinear systems. _916164
650		0	_aSystem identification. _94634
650		0	_aSystem identification. _94634
650		7	_aSCIENCE / System Theory. _2bisacsh _95324
650		7	_aTECHNOLOGY & ENGINEERING / Operations Research. _2bisacsh _95494
710	2		_aTaylor and Francis. _910719
776	0	8	_iPrint version: _z9781138064508
856	4	0	_uhttps://www.taylorfrancis.com/books/9781439896020 _zClick here to view.
942			_cEBK
999			_c72269 _d72269