By Topic

Algorithms and systolic architectures for multidimensional adaptive filtering via McClellan transformations

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

2 Author(s)
Shapiro, J.M. ; MIT Lincoln Lab., Lexington, MA, USA ; Staelin, D.H.

Algorithms are developed simultaneously with systolic architectures for multidimensional adaptive filtering Because of the extremely high data rate required for real-time video processing, there is a strong motivation to limit the size of any adaptation problem. Combining the McClellan transformations with systolic arrays to adapt and implement the least-squares filter yields a novel solution to the problem of adapting a large zero-phase finite impulse response (FIR) multidimensional filter, having arbitrary directional biases, with only a few parameters. These filters can be adapted abruptly on a block-by-block basis without causing blocking effects. After developing a basic processing element for a systolic array realization of the Chebyshev structure for the McClellan transformation, it is shown that for a given 2-D transformation function, the adaptation of the 1-D prototype filter becomes a small multichannel adaptation problem similar to adaptive array problems. A similar approach is also taken in developing algorithms to adapt the 2-D transformation function

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:2 ,  Issue: 1 )