By Topic

Generation of binary vectors that optimize a given weight function with application to soft-decision decoding

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
$33 $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)
A. Valembois ; Dept. of Electr. Eng., Hawaii Univ., Honolulu, HI, USA ; M. Fossorier

Many decoding algorithms need to compute some lists of binary vectors that minimize a given weight function. Furthermore, it is often desirable that these vectors are generated by increasing weight. The considered weight function is usually decreasing in the a priori likelihood that the vector yields correct decoding. We present a new technique to generate candidates for error patterns from the most a priori likely to the least, that proves significantly more efficient than any other known method

Published in:

Information Theory Workshop, 2001. Proceedings. 2001 IEEE

Date of Conference:

2001