Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

TLS linear prediction with optimum root selection for resolving closely space sinusoids

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
So, C.F. ; Dept. of Electr. Eng., Hong Kong Polytech. Univ., China ; Ng, S.C. ; Leung, S.H.

Total least square linear prediction has been successfully applied to frequency estimation for closely spaced sinusoids. In low signal to noise ratio, the resolving ability of TLS is degraded and extraneous roots of the predictor are close to unit circle. Hence the performance of total least square is severely degraded in low SNR. In this paper, a generalized total least squares method with a new root selection criterion, which is based on the envelope of the signal spectrum, is presented. An optimum procedure is introduced to provide a TLS solution that can perform closer to Cramer-Rao bound, particularly in low SNR.

Published in:

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on  (Volume:4 )

Date of Conference:

25-29 July 2004