Name
Abstract | ||
|---|---|---|
This paper presents a comparative performance analysis of two learning algorithms developed for the use in Cellular Neural Networks (CNN): the Center of Mass Algorithm, a back-propagation like technique, and an adaptation of the Genetic Algorithm. Both methods are applied for the training of a CNN built with Full Signal Range (FSR) cells, for the implementation of several well-known bipolar functions of image processing. Performance parameters such as total execution time, number of CNN runs and success rate are assessed in order to provide guidelines for the learning method choice. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LASCAS.2019.8667559 | 2019 IEEE 10th Latin American Symposium on Circuits & Systems (LASCAS) |
Keywords | Field | DocType |
Genetic algorithms,Training,Signal processing algorithms,Convergence,Computational modeling,Classification algorithms,Heuristic algorithms | Convergence (routing),Computer science,Image processing,Electronic engineering,Execution time,Artificial intelligence,Statistical classification,Cellular neural network,Center of mass,Genetic algorithm,Signal processing algorithms | Conference |
ISSN | ISBN | Citations |
2330-9954 | 978-1-7281-0453-9 | 1 |
PageRank | References | Authors |
0.41 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| fabian souza de andrade | 1 | 2 | 2.85 |
| edson pinto santana | 2 | 4 | 4.10 |
| Ana Isabela Araujo Cunha | 3 | 3 | 3.90 |
| Eduardo F. de Simas Filho | 4 | 1 | 0.41 |
| Gabriele Costa Gonçalves | 5 | 1 | 0.41 |
| Antônio José Sobrinho de Sousa | 6 | 1 | 0.41 |