On implementation of a least-squares based algorithm for noisy autoregressive signals

Author

Zheng, Wei Xing

Author_Institution

Dept. of Math., Western Sydney Univ., NSW, Australia

Volume

5

fYear

1998

fDate

31 May-3 Jun 1998

Firstpage

21

Abstract

A least-squares (LS) based algorithm for noisy autoregressive signals is recently proposed, which needs neither to prefilter noisy data nor to perform parameter extraction. In this paper, a more computationally efficient procedure for estimating the measurement noise variance is developed, and then an efficient implementation of the algorithm is presented. It is shown that this better way of implementation can considerably reduce the computational requirement of the LS based algorithm

Keywords

autoregressive processes; least squares approximations; noise; parameter estimation; signal processing; LS based algorithm; computationally efficient procedure; least-squares based algorithm; measurement noise variance estimation; noisy autoregressive signals; parameter extraction; Autoregressive processes; Electronics packaging; Mathematics; Noise cancellation; Noise measurement; Parameter extraction; Radar signal processing; Signal processing algorithms; Speech enhancement; Speech processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1998. ISCAS '98. Proceedings of the 1998 IEEE International Symposium on

Conference_Location

Monterey, CA

Print_ISBN

0-7803-4455-3

Type

conf

DOI

10.1109/ISCAS.1998.694396

Filename

694396