LEADER 05510nam 2200685 450 001 9910140271003321 005 20230803195607.0 010 $a1-118-53649-5 010 $a1-118-53648-7 010 $a1-118-53650-9 035 $a(CKB)2670000000547019 035 $a(EBL)1652084 035 $a(SSID)ssj0001132374 035 $a(PQKBManifestationID)11725639 035 $a(PQKBTitleCode)TC0001132374 035 $a(PQKBWorkID)11148281 035 $a(PQKB)11272882 035 $a(OCoLC)870248757 035 $a(MiAaPQ)EBC1652084 035 $a(DLC) 2014005560 035 $a(Au-PeEL)EBL1652084 035 $a(CaPaEBR)ebr10851654 035 $a(CaONFJC)MIL584512 035 $a(OCoLC)874322209 035 $a(EXLCZ)992670000000547019 100 $a20140407h20142014 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aIdentification of physical systems $eapplications to condition monitoring, fault diagnosis, softsensor, and controller design /$fRajamani Doraiswami, Chris Diduch and Maryhelen Stevenson 210 1$aChichester, West Sussex, United Kingdom :$cJohn Wiley & Sons,$d2014. 210 4$dİ2014 215 $a1 online resource (538 p.) 300 $aDescription based upon print version of record. 311 $a1-119-99012-2 320 $aIncludes bibliographical references and index. 327 $aIDENTIFICATION OF PHYSICAL SYSTEMS; Contents; Preface; Nomenclature; 1 Modeling of Signals and Systems; 1.1 Introduction; 1.2 Classification of Signals; 1.2.1 Deterministic and Random Signals; 1.2.2 Bounded and Unbounded Signal; 1.2.3 Energy and Power Signals; 1.2.4 Causal, Non-causal, and Anti-causal Signals; 1.2.5 Causal, Non-causal, and Anti-causal Systems; 1.3 Model of Systems and Signals; 1.3.1 Time-Domain Model; 1.3.2 Frequency-Domain Model; 1.4 Equivalence of Input-Output and State-Space Models; 1.4.1 State-Space and Transfer Function Model 327 $a1.4.2 Time-Domain Expression for the Output Response1.4.3 State-Space and the Difference Equation Model; 1.4.4 Observer Canonical Form; 1.4.5 Characterization of the Model; 1.4.6 Stability of (Discrete-Time) Systems; 1.4.7 Minimum Phase System; 1.4.8 Pole-Zero Locations and the Output Response; 1.5 Deterministic Signals; 1.5.1 Transfer Function Model; 1.5.2 Difference Equation Model; 1.5.3 State-Space Model; 1.5.4 Expression for an Impulse Response; 1.5.5 Periodic Signal; 1.5.6 Periodic Impulse Train; 1.5.7 A Finite Duration Signal; 1.5.8 Model of a Class of All Signals 327 $a1.5.9 Examples of Deterministic Signals1.6 Introduction to Random Signals; 1.6.1 Stationary Random Signal; 1.6.2 Joint PDF and Statistics of Random Signals; 1.6.3 Ergodic Process; 1.7 Model of Random Signals; 1.7.1 White Noise Process; 1.7.2 Colored Noise; 1.7.3 Model of a Random Waveform; 1.7.4 Classification of the Random Waveform; 1.7.5 Frequency Response and Pole-Zero Locations; 1.7.6 Illustrative Examples of Filters; 1.7.7 Illustrative Examples of Random Signals; 1.7.8 Pseudo Random Binary Sequence (PRBS); 1.8 Model of a System with Disturbance and Measurement Noise 327 $a1.8.1 Input-Output Model of the System1.8.2 State-Space Model of the System; 1.8.3 Illustrative Examples in Integrated System Model; 1.9 Summary; References; Further Readings; 2 Characterization of Signals: Correlation and Spectral Density; 2.1 Introduction; 2.2 Definitions of Auto- and Cross-Correlation (and Covariance); 2.2.1 Properties of Correlation; 2.2.2 Normalized Correlation and Correlation Coefficient; 2.3 Spectral Density: Correlation in the Frequency Domain; 2.3.1 Z-transform of the Correlation Function; 2.3.2 Expressions for Energy and Power Spectral Densities 327 $a2.4 Coherence Spectrum2.5 Illustrative Examples in Correlation and Spectral Density; 2.5.1 Deterministic Signals: Correlation and Spectral Density; 2.5.2 Random Signals: Correlation and Spectral Density; 2.6 Input-Output Correlation and Spectral Density; 2.6.1 Generation of Random Signal from White Noise; 2.6.2 Identification of Non-Parametric Model of a System; 2.6.3 Identification of a Parametric Model of a Random Signal; 2.7 Illustrative Examples: Modeling and Identification; 2.8 Summary; 2.9 Appendix; References; 3 Estimation Theory; 3.1 Overview 327 $a3.2 Map Relating Measurement and the Parameter 330 $a Develops a systematic and a unified approach to the problem of physical system identification and its practical applications There is a need for a book which develops a systematic and a unified approach to the problem of physical system identification and its practical applications. Identification of Physical Systems addresses this need, developing identification theory using a coherent, simple and yet rigorous approach. Starting with a least-squares method, the author develops various schemes to address the issues of accuracy, variation in the operating regimes, closed loop and inter 606 $aSystems engineering 606 $aSystems engineering$xMathematics 615 0$aSystems engineering. 615 0$aSystems engineering$xMathematics. 676 $a620.001/1 700 $aDoraiswami$b Rajamani$0962673 702 $aStevenson$b Maryhelen 702 $aDiduch$b Chris 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910140271003321 996 $aIdentification of physical systems$92182876 997 $aUNINA