A new classifier based on associative memories

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

The Lernmatrix, which is the first known model of associative memory, is an heteroassociative memory, but it can also act as a binary pattern classifier depending on the choice of the output patterns. However, this model suffers two great problems: saturation and imperfect recall of some of the associations, even in the fundamental set, depending on the associations. In this work, a modification to the original Lernmatrix recall phase algorithm is presented. This modification improves the recalling capacity of the original model Experimental results show this improvement

Original languageEnglish
Title of host publicationProceedings - 15th International Conference on Computing, CIC 2006
Pages55-59
Number of pages5
DOIs
StatePublished - 2006
Event15th International Conference on Computing, CIC 2006 - Mexico City, Mexico
Duration: 21 Nov 200624 Nov 2006

Publication series

NameProceedings - 15th International Conference on Computing, CIC 2006

Conference

Conference15th International Conference on Computing, CIC 2006
Country/TerritoryMexico
CityMexico City
Period21/11/0624/11/06

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