LEADER 02350nam 2200469 450 001 9910467394603321 005 20200520144314.0 010 $a1-119-54640-0 010 $a1-119-54641-9 035 $a(CKB)4100000007814836 035 $a(MiAaPQ)EBC5731871 035 $a(CaSebORM)9781119546368 035 $a(Au-PeEL)EBL5731871 035 $a(OCoLC)1057242269 035 $a(EXLCZ)994100000007814836 100 $a20190329d2019 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aModel identification and data analysis /$fSergio Bittanti 205 $a1st edition 210 1$aHoboken, NJ :$cWiley,$d[2019] 210 4$dİ2019 215 $a1 online resource (419 pages) 311 $a1-119-54636-2 330 $aThis book is about constructing models from experimental data. It covers a range of topics, from statistical data prediction to Kalman filtering, from black-box model identification to parameter estimation, from spectral analysis to predictive control. Written for graduate students, this textbook offers an approach that has proven successful throughout the many years during which its author has taught these topics at his University. The book: Contains accessible methods explained step-by-step in simple terms Offers an essential tool useful in a variety of fields, especially engineering, statistics, and mathematics Includes an overview on random variables and stationary processes, as well as an introduction to discrete time models and matrix analysis Incorporates historical commentaries to put into perspective the developments that have brought the discipline to its current state Provides many examples and solved problems to complement the presentation and facilitate comprehension of the techniques presented 606 $aSystem identification$xMathematical models 606 $aQuantitative research 608 $aElectronic books. 615 0$aSystem identification$xMathematical models. 615 0$aQuantitative research. 676 $a003.1 700 $aBittanti$b Sergio$09717 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910467394603321 996 $aModel identification and data analysis$92177864 997 $aUNINA