By Topic

On a method of calculating the event error probability of convolutional codes with maximum likelihood decoding (Corresp.)

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)

Maximum likelihood (ML) decoding of short constraint length convolutional codes became feasible with the invention of the Viterbi decoder. Several authors have since upper bounded the performance of ML decoders. A method to calculate the event error probability of an ML decoder for convolutional codes is described.

Published in:

Information Theory, IEEE Transactions on  (Volume:25 ,  Issue: 6 )