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, ...

Nonparametric System Identification 2012, Cambridge University Press, Cambridge

ISBN-13: 9781107410626

Trade paperback

Select
Nonparametric System Identification 2008, Cambridge University Press, Cambridge

ISBN-13: 9780521868044

Hardcover

Select