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In order to prevent premature convergence of constriction factor particle swarm optimization (cfPSO), an improved version of cfPSO is presented in this paper. Firstly, a new standard of premature convergence was set up to determine the algorithm relapsing into local extremum. Then an improved re-initialization method was design to insure the uniform distribution of swarm in search space. In this method,...
Inspired by the diffusion movement phenomenon of the molecules, this paper presents a diffusion-repulsion particle swarm optimization (DRPSO). The proposed new algorithm (DRPSO) includes attraction and repulsion (or migration) phases. Once the diversity of population becomes too low, the individuals will be dispersed and carry out diffusion movement, while if the diversity of population becomes too...
The difficulty for accurate determination of the angles of arrival (AOA) of signals arises from the optimization of likelihood functions of high dimension. Usually, a gradient-based technique is employed to find the optimum of the function. However, this method requires heavy computational work and the differentiability of the likelihood function. This paper presents two gradient-free methods: One...
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