REGRESSOR SELECTION WITH THE ANALYSIS OF VARIANCE METHOD
Ingela Lind
Division of Automatic Control, Department of Electrical Engineering, Linköping University, SE-581 83 Linköping, Sweden. E-mail: ingela@isy.liu.se
Identification of non-linear finite impulse response (N-FIR) models is studied. In particular the selection of model structure, i.e., to find the best regressors, is examined. In this paper it is shown that a statistical method, the analysis of variance, is a better alternative than exhaustive search among all possible regressors, in the identification of the structure of non-linear FIR-models. The method is evaluated for different conditions on the input signal to the system. The results will serve as a foundation for the extension of the ideas to non-linear autoregressive processes.
Keywords: Time delay estimation, Time lag, Identification, Non-linear models, Analysis of variance
Session slot T-Th-E01: Identification of Nonlinear Systems III/Area code 3a : Modelling, Identification and Signal Processing

|