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008 150903s2011 xxk| o |||| 0|eng d
020 _a9780857295224
_99780857295224
024 7 _a10.1007/9780857295224
_2doi
035 _avtls000333913
039 9 _a201509030242
_bVLOAD
_c201404130557
_dVLOAD
_c201404092346
_dVLOAD
_y201402041135
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTJ212-225
100 1 _aKeesman, Karel J.
_eautor
_9306572
245 1 0 _aSystem Identification :
_bAn Introduction /
_cby Karel J. Keesman.
264 1 _aLondon :
_bSpringer London,
_c2011.
300 _axxvI, 323 páginas 109 ilustraciones, 37 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aAdvanced Textbooks in Control and Signal Processing,
_x1439-2232
500 _aSpringer eBooks
505 0 _aIntroduction -- Part I: Data-based Identification -- System Response Methods -- Frequency Response Methods -- Correlation Methods -- Part II: Time-invariant Systems Identification -- Static Systems Identification -- Dynamic Systems Identification -- Part III: Time-varying Systems Identification -- Time-varying Static Systems Identification -- Time-varying Dynamic Systems Identification -- Part IV: Model Validation -- Model Validation Techniques -- Part V: Appendices: Matrix Algebra; Statistics; Laplace, Fourier and z-Transforms; Bode Diagrams; Shift Operator Calculus; Recursive Least-squares Derivation; Dissolved Oxygen Data.
520 _aSystem Identification: an Introduction shows the (student) reader how to approach the system identification problem in a systematic fashion. Essentially, system identification is an art of modelling, where appropriate choices have to be made concerning the level of approximation, given prior system’s knowledge, noisy data and the final modelling objective. The system identification process is basically divided into three steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. The book contains four parts covering: ·        data-based identification – non-parametric methods for use when prior system knowledge is very limited; ·        time-invariant identification for systems with constant parameters; ·        time-varying systems identification, primarily with recursive estimation techniques; and ·        model validation methods. The book uses essentially semi-physical or grey-box modelling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input–output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various model applications, as control, prediction and experimental design, with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors’ Solutions Manual is available from www.springer.com/978-0-85729-521-7) will both help students to assimilate what they have learnt and make the book suitable for self-tuition by practitioners looking to brush up on modern techniques. Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification: an Introduction will help academic instructors teaching control-related courses to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.  
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780857295217
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-85729-522-4
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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