Name
Title | ||
|---|---|---|
Generalised Opposition-Based Differential Evolution For Frequency Modulation Parameter Optimisation |
Abstract | ||
|---|---|---|
This paper presents an improved differential evolution (DE) algorithm to solve frequency modulation (FM) parameter optimisation problems. The proposed approach is called generalised opposition-based differential evolution (GODE), which employs generalised opposition-based learning (GOBL) to accelerate the convergence rate of original DE. To solve the FM problem, three different kinds of parameter optimisation models are verified in the experiments. Simulation results show that our approach achieves better matching than three other similar algorithms. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1504/IJMIC.2013.053543 | INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL |
Keywords | Field | DocType |
differential evolution, generalised opposition-based learning, GOBL, frequency modulation parameter optimisation, global optimisation | Control theory,Differential evolution,Rate of convergence,Frequency modulation,Opposition (planets),Mathematics | Journal |
Volume | Issue | ISSN |
18 | 4 | 1746-6172 |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hui Wang | 1 | 277 | 17.29 |
| Wenjun Wang | 2 | 11 | 1.99 |
| Huasheng Zhu | 3 | 2 | 0.37 |
| Hui Sun | 4 | 3 | 1.05 |