@InProceedings{EsmiSussSand:2014:InTuEq,
author = "Esmi, E. and Sussner, P. and Sandri, Sandra Aparecida",
affiliation = "{Universidade Estadual de Campinas (UNICAMP)} and {Universidade
Estadual de Campinas (UNICAMP)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)}",
title = "An introduction to tunable equivalence fuzzy associative
memories",
booktitle = "Proceedings...",
year = "2014",
pages = "1604--1611",
organization = "2014. IEEE International Conference on Fuzzy Systems,
(FUZZ-IEEE)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
keywords = "Associative processing, Associative storage, Equivalence classes,
Associative memory models, Computational effort, Fuzzy associative
memory, Fuzzy equivalence, Hidden layers, Hidden nodes, Training
algorithms, Training data, Fuzzy neural networks.",
abstract = "In this paper, we present a new class of fuzzy associative
memories (FAMs) called tunable equivalence fuzzy associative
memories, for short tunable E-FAMs or TE-FAMs, that belong to the
class \Θ-fuzzy associative memories (\Θ-FAMs). Recall
that 0-FAMs represent fuzzy neural networks having a competitive
hidden layer and weights that can be adjusted via a training
algorithm. Like any associative memory model, \Θ-FAMs depend
on the specification of a fundamental memory set. In contrast to
other \Θ-FAM models, TE-FAMs make use of parametrized fuzzy
equivalence measures that are associated with the hidden nodes and
allow for the extraction of a fundamental memory set from the
training data. The use of a smaller fundamental memory set than in
previous articles on \Θ-FAMs reduces the computational
effort involved in deriving the weights without decreasing the
quality of the results.",
conference-location = "Beijing",
conference-year = "July 6-11, 2014.",
doi = "10.1109/FUZZ-IEEE.2014.6891851",
url = "http://dx.doi.org/10.1109/FUZZ-IEEE.2014.6891851",
isbn = "9781479920723",
issn = "1098-7584",
label = "scopus 2015-01 EsmiSussSand:2014:InTuEq",
language = "en",
urlaccessdate = "27 abr. 2024"
}