Nonlinear System Identification by Haar Wavelets, 2013
Lecture Notes in Statistics Series, Vol. 210

?In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account. The generic, black-box model based on Volterra and Wiener series is capable of representing fairly complicated nonlinear and dynamic interactions, however, the resulting identification algorithms are impractical, mainly due to their computational complexity. One of the alternatives offering fast identification algorithms is the block-oriented approach, in which systems of relatively simple structures are considered. The book provides nonparametric identification algorithms designed for such systems together with the description of their asymptotic and computational properties. ? ?

Dr. Przemysław Śliwiński is an assistant professor at the Wrocław University of Technology, where he received his master’s degree in 1996 and his PhD in 2000. For his master’s degree he developed an integrated development environment with a software emulator of a micro-controller. His PhD dissertation addressed the problems of nonlinear system identification using linear wavelet estimation algorithms.

Provides nonparametric algorithms based on standard and unbalanced Haar bases Demonstrates applicability of nonlinear approximation schemes to nonlinear system identification Offers fast identification routines Includes supplementary material: sn.pub/extras