| Full text | |
| Author(s): |
de Souza, Aline Cristina
;
Valle, Marcos Eduardo
;
Barreto, GA
;
Coelho, R
Total Authors: 4
|
| Document type: | Journal article |
| Source: | FUZZY INFORMATION PROCESSING, NAFIPS 2018; v. 831, p. 12-pg., 2018-01-01. |
| Abstract | |
In this paper we introduce the class of fuzzy kernel associative memories (fuzzy KAMs). Fuzzy KAMs are derived from single-step generalized exponential bidirectional fuzzy associative memories by interpreting the exponential of a fuzzy similarity measure as a kernel function. The output of a fuzzy KAM is obtained by summing the desired responses weighted by a normalized evaluation of the kernel function. Furthermore, in this paper we propose to estimate the parameter of a fuzzy KAM by maximizing the entropy of the model. We also present two approaches for pattern classification using fuzzy KAMs. Computational experiments reveal that fuzzy KAM-based classifiers are competitive with well-known classifiers from the literature. (AU) | |
| FAPESP's process: | 15/00745-1 - A Study on Recurrent Exponential Fuzzy Associative Memories, Their Generalizations, and Applications |
| Grantee: | Aline Cristina de Souza |
| Support Opportunities: | Scholarships in Brazil - Doctorate |