By Topic

A fast covariance type algorithm for sequential least-squares filtering and prediction

Sign In

Full text access may be available.

To access full text, please use your member or institutional sign in.

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)
Kalouptsidis, N. ; University of Athens, Athens, Greece ; Carayannis, G. ; Manolakis, D.

Fast implementation of sequential least-squares (LS) algorithms is of great importance in various applications of signal processing, estimation, system identification, and control. The purpose of this note is the introduction of an efficient sequential LS algorithm for multichannel unwindowed signals (covariance case). The new scheme, in the single channel case, requires 10 m MADPR (multiplications and divisions per recursion), m being the number of estimated parameters. This offers a saving of 5 m MADPR compared to other existing algorithms.

Published in:

Automatic Control, IEEE Transactions on  (Volume:29 ,  Issue: 8 )