14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper FrB1.3

Hsu, Kenneth (Univ. of California at Berkeley), Vincent, Tyrone (Colorado School of Mines), Poolla, Kameshwar (Univ. of California at Berkeley)

A Kernel Based Approach to Structured Nonlinear System Identification Part II: Convergence and Consistency

Scheduled for presentation during the Regular Session "Kernel Based Nonlinear System Identification" (FrB1), Friday, March 31, 2006, 16:10−16:30, Concert Hall

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on April 12, 2021

Keywords Nonlinear System Identification, Nonparametric Methods, Identifiability


In a companion paper (Hsu et al., 2005c), an algorithm for the identification of structured nonlinear systems was proposed and its computational properties were explored. In this paper, we continue the investigation and formalize notions of identifiability and persistence of excitation. Conditions under which the estimated nonlinearity converges uniformly to the true nonlinearity are developed for a class of kernel based dispersion functions.