By Topic

A systolic architecture for gradient based adaptive subspace tracking algorithms

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

1 Author(s)
Bin Yang ; Dept. of Electr. Eng., Ruhr Univ. Bochum, Germany

Subspace estimation plays an important role in a variety of modern signal processing applications. In an unknown and possibly changing environment, adaptive algorithms which are computationally efficient, numerically stable, and easy implementable in hardware are highly desirable. The author shows that gradient type adaptive algorithms are not only competitive in subspace tracking, but also advantageous in both the computational complexity and performance robustness. A novel systolic architecture for implementing these algorithms, with a high processor utilization, is presented

Published in:

VLSI Signal Processing, VI, 1993., [Workshop on]

Date of Conference:

20-22 Oct 1993