Title :
On implementation of a least-squares based algorithm for noisy autoregressive signals
Author_Institution :
Dept. of Math., Western Sydney Univ., NSW, Australia
fDate :
31 May-3 Jun 1998
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;
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
DOI :
10.1109/ISCAS.1998.694396
