Paper Info
Title
Fuzzy associative memories based on subsethood and similarity measures with applications to speaker identification
Abstract
Recently, we presented a non-distributive fuzzy associative memory (FAM) called the Kosko subsethood FAM, for short KS-FAM. This model can be classified as a morphological neural network because it is based on computing the degree of fuzzy inclusion or subsethood of patterns and this operation can be considered an erosion in fuzzy mathematical morphology. In this paper, we introduce a whole range of extensions of the KS-FAM called S-FAMs, dual S-FAMs, and SM-FAMs. Here, the acronyms S-FAM and SM-FAM stand for respectively subsethood FAM and similarity measure FAM. The new models share some properties with the KS-FAM such as unlimited absolute storage capacity and a small number of spurious memories. The paper finishes some experimental results concerning the problem of text-independent speaker identification. For comparative purposes, we included the recognition rates obtained by some well-known classifiers from the literature.
Year
DOI
Venue
2012
10.1007/978-3-642-28931-6_46
HAIS (2)
Keywords
Field
DocType
dual s-fams,subsethood fam,speaker identification,acronyms s-fam,fuzzy mathematical morphology,non-distributive fuzzy associative memory,similarity measure fam,sm-fam stand,short ks-fam,fuzzy inclusion,kosko subsethood fam,inclusion
Small number,Fuzzy associative memory,Speaker identification,Associative property,Pattern recognition,Similarity measure,Computer science,Fuzzy logic,Artificial intelligence,Artificial neural network,Spurious relationship,Machine learning
Conference
Volume
ISSN
Citations 
7209
0302-9743
8
PageRank 
References 
Authors
0.48
20
5
Name
Order
Citations
PageRank
Estevão Esmi1103.89
Peter Sussner288059.25
Marcos Eduardo Valle322617.84
Fábio Sakuray480.82
Laécio C. Barros511521.74