| Full text | |
| Author(s): |
Fantinato, Denis G.
;
Neves, Aline
;
Silva, Daniel G.
;
Attux, Romis
;
Ueda, N
;
Watanabe, S
;
Matsui, T
;
Chien, JT
;
Larsen, J
Total Authors: 9
|
| Document type: | Journal article |
| Source: | 2017 IEEE 27TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING; v. N/A, p. 6-pg., 2017-01-01. |
| Abstract | |
In communication systems, the study of elements and structures defined over Galois fields are generally limited to data coding. However, in this work, a novel perspective that combines data coding and channel equalization is considered to compose a simplified communication system over the field. Besides the coding advantages, this framework is able to restore distortions or malfunctioning processes, and can be potentially applied in network coding models. Interestingly, the operation of the equalizer is possible from a blind standpoint through the exploration of the redundant information introduced by the encoder. More specifically, we define a blind equalization criterion based on the matching of probability mass functions (PMFs) via the Kullback-Leibler divergence. Simulations involving the main aspects of the equalizer and the criterion are performed, including the use of a genetic algorithm to aid the search for the solution, with promising results. (AU) | |
| FAPESP's process: | 17/11488-5 - Multivariate Analysis of the Data Temporal Structure for Blind Source Separation in the Context of Nonlinear Mixtures and of Multiple Datasets |
| Grantee: | Denis Gustavo Fantinato |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |
| FAPESP's process: | 13/14185-2 - New Methods for Adaptive Equalization Based on Information Theoretic Learning |
| Grantee: | Denis Gustavo Fantinato |
| Support Opportunities: | Scholarships in Brazil - Doctorate |