Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

Enhancing Performance of Relational Fuzzy Neural Networks with Square BK-Products

Authors
Warren L. Davis IV 0, Ladislav Kohout
Corresponding Author
Warren L. Davis IV
0Florida State University
Available Online October 2006.
DOI
https://doi.org/10.2991/jcis.2006.107How to use a DOI?
Keywords
Fuzzy Logic, Pattern Classification, Neural Network
Abstract
In this paper, we extend research done in max-min fuzzy neural networks in several important ways. We replace max and min operations use in the fuzzy operations by more general t-norms and co-norms, respectively. In addition, instead of the Łukasiewicz equivalence connective used in the network of Reyes-Garcia and Bandler, we employ in our hybridization a variety of equivalence connectives. We explore the effectiveness of this network in the domain of phoneme recognition and diabetes data. We find increased classification ability in many cases, as well as great potential for further expansion of the use of fuzzy operations in the field of pattern recognition.
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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Part of series
Advances in Intelligent Systems Research
Publication Date
October 2006
ISBN
978-90-78677-01-7
ISSN
1951-6851
DOI
https://doi.org/10.2991/jcis.2006.107How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Warren L. Davis IV
AU  - Ladislav Kohout
PY  - 2006/10
DA  - 2006/10
TI  - Enhancing Performance of Relational Fuzzy Neural Networks with Square BK-Products
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.107
DO  - https://doi.org/10.2991/jcis.2006.107
ID  - DavisIV2006/10
ER  -