Conjugate gradient method in adaptive bilinear filtering

Author

Bose, Tamal ; Chen, Mei-Qin

Author_Institution

Dept. of Electr. Eng., Colorado Univ., Denver, CO, USA

Volume

43

Issue

6

fYear

1995

fDate

6/1/1995 12:00:00 AM

Firstpage

1503

Lastpage

1508

Abstract

The application of the conjugate gradient (CG) method for the identification of bilinear systems is investigated. An algorithm based on the CG method is developed for adaptive bilinear digital filtering. In this algorithm, the optimization is done over blocks of input and output data rather than a single pair of data. However, only one iteration and coefficient update is done for every sample of data. This, coupled with the fact that the CG method used does not require a line search makes it very efficient in computation. Simulation results show that this algorithm outperforms the LMS and RLS algorithms in terms of speed of convergence. A preconditioning technique is also applied to further accelerate the convergence in some cases

Keywords

adaptive filters; bilinear systems; computational complexity; conjugate gradient methods; convergence of numerical methods; identification; interpolation; nonlinear filters; optimisation; recursive filters; signal sampling; adaptive bilinear filtering; bilinear systems; coefficient update; computation efficiency; conjugate gradient method; convergence; data sample; digital filtering; identification; input data blocks; iteration; optimization; output data blocks; preconditioning technique; Adaptive filters; Character generation; Computational modeling; Convergence; Digital filters; Filtering algorithms; Gradient methods; Least squares approximation; Nonlinear systems; Resonance light scattering;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.388864

Filename

388864