DocumentCode :
2832554
Title :
A New Classifier Based on Associative Memories
Author :
Román-Godínez, Israel ; López-Yánez, Itzamá ; Yánez-Márquez, Cornelio
Author_Institution :
Centra de Investigation en Comput., Instituto Politecnico Nat., Mexico
fYear :
2006
fDate :
Nov. 2006
Firstpage :
55
Lastpage :
59
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
Keywords :
content-addressable storage; matrix algebra; pattern classification; Lernmatrix recall phase algorithm; associative memories; binary pattern classifier; heteroassociative memory; Associative memory; Matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, 2006. CIC '06. 15th International Conference on
Conference_Location :
Mexico City
Print_ISBN :
0-7695-2708-6
Type :
conf
DOI :
10.1109/CIC.2006.13
Filename :
4023788
Link To Document :
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