| Revue: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560365 |
| ISSN: | 1405-5546 |
| Autores: | Sacanamboy, Maribell1 Bolaños, Freddy2 Bernal, Alvaro3 |
| Instituciones: | 1Pontificia Universidad Javeriana, Electronics and Computer Sciences Department, Cali, Bogotá. Colombia 2Universidad Nacional de Colombia, Electrical Energy and Automation Department, Medellín. Colombia 3Universidad del Valle, Electrical and Electronics Engineering School, Cali, Valle del Cauca. Colombia |
| Año: | 2018 |
| Periodo: | Jul-Sep |
| Volumen: | 22 |
| Número: | 3 |
| Paginación: | 985-996 |
| País: | México |
| Idioma: | Inglés |
| Resumen en inglés | This paper describes the use of Renyi’s entropy as a way to improve the convergence time of the Population-Based Incremental Learning (PBIL) optimization algorithm. As a case study, the algorithm was used in a hierarchical wireless network-on-chip (WiNoC) for the sake of performing the optimal task mapping of applications. Two versions of Renyi’s entropy are used and compared to the more traditional Shannon formulation. The obtained results are promising and suggest that Renyi’s entropy may help to reduce the PBIL convergence time, without degrading the quality of the found solutions. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial |
| Keyword: | Renyi’s entropy, PBIL, Wireless network-on-chip (WiNoC), Mapping, Convergence time, Artificial intelligence |
| Texte intégral: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
