14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper ThB1.6

Nazin, Alexander (Inst. of Control Sciences), Roll, Jacob (Linköping Univ.), Ljung, Lennart (Linköping Univ.)

Direct Weight Optimization for Approximately Linear Functions: Optimality and Design

Scheduled for presentation during the Invited Session "Nonlinear System Identification II" (ThB1), Thursday, March 30, 2006, 17:10−17:30, Concert Hall

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

This information is tentative and subject to change. Compiled on July 22, 2018

Keywords Nonlinear System Identification, Nonparametric Methods


The Direct Weight Optimization (DWO) approach to estimating a regression function is studied here for the class of approximately linear functions, i.e., functions whose deviation from an affine function is bounded by a known constant. Upper and lower bounds for the asymptotic maximum MSE are given, some of which also hold in the non-asymptotic case and for an arbitrary fixed design. Their coincidence is then studied. Particularly, under mild conditions, it can be shown that there is always an interval in which the DWO-optimal estimator is optimal among all estimators. Experiment design issues are also studied.