Nonparametric System Identification

Inbunden, Engelska, 2008

AvWlodzimierz Greblicki,Miroslaw Pawlak,Poland) Greblicki, Wlodzimierz (Politechnika Wroclawska,Canada) Pawlak, Miroslaw (University of Manitoba

1 379 kr

Beställningsvara. Skickas inom 7-10 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Finns i fler format (1)

Häftad

899 kr

Skickas inom 7-10 vardagar

Presenting a thorough overview of the theoretical foundations of non-parametric system identification for nonlinear block-oriented systems, this book shows that non-parametric regression can be successfully applied to system identification, and it highlights the achievements in doing so. With emphasis on Hammerstein, Wiener systems, and their multidimensional extensions, the authors show how to identify nonlinear subsystems and their characteristics when limited information exists. Algorithms using trigonometric, Legendre, Laguerre, and Hermite series are investigated, and the kernel algorithm, its semirecursive versions, and fully recursive modifications are covered. The theories of modern non-parametric regression, approximation, and orthogonal expansions, along with new approaches to system identification (including semiparametric identification), are provided. Detailed information about all tools used is provided in the appendices. This book is for researchers and practitioners in systems theory, signal processing, and communications and will appeal to researchers in fields like mechanics, economics, and biology, where experimental data are used to obtain models of systems.

Produktinformation

Utgivningsdatum2008-06-16
Mått182 x 262 x 31 mm
Vikt990 g
FormatInbunden
SpråkEngelska
Antal sidor400
FörlagCambridge University Press
ISBN9780521868044

Tillhör följande kategorier

Wlodzimierz Greblicki is a professor at the Institute of Computer Engineering, Control, and Robotics at the Wroclaw University of Technology, Poland. Miroslaw Pawlak is a professor in the Department of Electrical and Computer Engineering at the University of Manitoba, Canada. He was awarded his PhD in 1982 from the Wroclaw University of Technology, Poland. Both authors have published extensively over the years in the area of non-parametric theory and applications.

1. Introduction; 2. Discrete-time Hammerstein systems; 3. Kernel algorithms; 4. Semi-recursive kernel algorithms; 5. Recursive kernel algorithms; 6. Orthogonal series algorithms; 7. Algorithms with ordered observations; 8. Continuous-time Hammerstein systems; 9. Discrete-time Wiener systems; 10. Kernel and orthogonal series algorithms; 11. Continuous-time Wiener system; 12. Other block-oriented nonlinear systems; 13. Multivariate nonlinear block-oriented systems; 14. Semiparametric identification; Appendices.

Review of the hardback: 'All chapters end with precise technical derivations of the presented material and bibliographical notes providing numerous references to the related literature … The monograph fills the gap in the system identification monographic literature dealing mainly with the parametric approach, and can be recommended for researchers and practitioners interested in system identification problems where a priori information is very limited and only experimental data can be reliably used to recover system models.' Zentralblatt MATH