Adaptive bilinear inverse filtering

Author

Ahmed, Barran M. ; Rauf, Fawad

Author_Institution

Dept. of Electron. & Comput. Sci., Boston Univ., MA, USA

Volume

4

fYear

1992

fDate

23-26 Mar 1992

Firstpage

185

Abstract

A parsimonious adaptive nonlinear filtering structure based on bilinear models is presented. A state-dependent embedding for developing nonlinear filters is presented. It is used to develop a computationally efficient bilinear adaptive filter which requires only local adaptation. Modularity and local connectivity make the structure amenable to VLSI implementation. In contrast to previous input-output pair (system identification) frameworks, an inverse filtering problem is considered where only output is observable. The adaptation is shown to be dependent on both past and present gradients

Keywords

adaptive filters; digital filters; filtering and prediction theory; VLSI; adaptive bilinear inverse filtering; adaptive nonlinear filtering structure; bilinear adaptive filter; bilinear models; local adaptation; local connectivity; nonlinear filters; state-dependent embedding; Adaptive filters; Context modeling; Filtering; Neural networks; Nonlinear control systems; Nonlinear filters; Nonlinear systems; System identification; Vectors; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on

Conference_Location

San Francisco, CA

ISSN

1520-6149

Print_ISBN

0-7803-0532-9

Type

conf

DOI

10.1109/ICASSP.1992.226455

Filename

226455