Generalised opposition-based differential evolution for frequency modulation parameter optimisation
Hui Wang, Wenjun Wang, Huasheng Zhu, Hui Sun · International Journal of Modelling Identification and Control · 2013
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.