DocumentCode :
2827848
Title :
Preconditioned conjugate gradient methods for adaptive filtering
Author :
Hull, Andrew W. ; Jenkins, W. Kenneth
Author_Institution :
Illinois Univ., Urbana, IL, USA
fYear :
1991
fDate :
11-14 Jun 1991
Firstpage :
540
Abstract :
The method of preconditioned conjugate gradients (PCGs) is proposed for solving the problem of adaptive filtering. Considered as an iterative algorithm, the PCG algorithm is asymptotically efficient. It is suggested for use in applications requiring very high order adaptive filters. The method is also extended to the IIR (infinite impulse response) case. Application to the PCG algorithm to very long filters is suggested to exploit the fact that the number of iterations of the PCG algorithm until convergence is independent of the filter order. In a block algorithm, then, increasing filter length increases the efficiency of the algorithm
Keywords :
adaptive filters; digital filters; filtering and prediction theory; adaptive filtering; asymptotically efficient; filter length; filter order; high order adaptive filters; iterative algorithm; long filters; preconditioned conjugate gradient methods; Adaptive algorithm; Adaptive filters; Application software; Character generation; Computational complexity; Convergence; Costs; Gradient methods; Iterative algorithms; Signal processing algorithms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1991., IEEE International Sympoisum on
Print_ISBN :
0-7803-0050-5
Type :
conf
DOI :
10.1109/ISCAS.1991.176392
Filename :
176392
Link To Document :
بازگشت