Title :
Classification of very large bit size patterns
Author_Institution :
Sch. of Eng., Sussex Univ., Brighton, UK
fDate :
10/1/1998 12:00:00 AM
Abstract :
The author presents the results of tests which extend the published input size of associative list memory (ALM) by two orders of magnitude. In particular, ALM is shown to approach the optimum classifier performance when classifying inputs as large as 105 bits
Keywords :
content-addressable storage; pattern classification; associative list memory; input size; optimum classifier performance; very large bit size patterns;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19980622
