By Topic

A New Heuristic for Inferring Regular Grammars

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

1 Author(s)
Stephen Y. Itoga ; Department of Information and Computer Science, University of Hawaii, Honolulu, HI 96822.

Modifications to a grammatical inference scheme by Feldman et al. are presented. A comparison of the relative performance of the original and modified schemes is made using the complexity measures of Feldman and Wharton. The case where a complex model is used to generate the sample set is then analyzed. A set of 104 samples was found that trained the program to infer the grammar that corresponded to the original model. The results of a study of the performance of this algorithm when there is a large number of samples is then presented. The major conclusion of this study is that the modified scheme has a superior performance on small sample sets but is highly unsuitable for large ones.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:PAMI-3 ,  Issue: 2 )