Time-varying quadratic model selection using wavelet packets

Author

Green, Matthew

Author_Institution

Australian Telecommun. Cooperative Res. Center, Curtin Univ. of Technol., Perth, WA, Australia

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

345

Lastpage

348

Abstract

Model selection and system identification for cases where the model is required to have both characteristics of time-variance and nonlinearity is considered. To enable identification from a single input/output observation record, the time-variation is approximated by a weighted sum of orthogonal sequences. Wavelet packets are chosen for these sequences and an adapted basis for each time-varying coefficient is selected via the best basis algorithm. Individual wavelet packets are then selected via a multiple hypothesis test which determines those packets that are significant to each approximation, and which may be discarded from the model

Keywords

dispersive channels; identification; multipath channels; sequences; time-varying channels; wavelet transforms; best basis algorithm; dispersive time-varying communication channel; mobile communications; multiple hypothesis test; nonlinear model; nonlinearity; quadratic Volterra model; single input/output observation record; system identification; time-varying coefficient; time-varying quadratic model selection; wavelet packets; weighted orthogonal sequences; Australia; Communication channels; Ear; Hydrogen; Kernel; Least squares approximation; System identification; Time varying systems; Wavelet analysis; Wavelet packets;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Print_ISBN

0-7803-7011-2

Type

conf

DOI

10.1109/SSP.2001.955293

Filename

955293