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Regarding the complementarity of particle swarm optimization (PSO) and differential evolution (DE) and the complementarity of different differential evolutionary modes of DE, hybrid PSODE with three populations based on multiple differential evolutionary models is proposed. The algorithm effectively combines PSO and DE of two different evolutionary modes, improving local and global optimization ability...
This paper presents a new variation of particle swarm optimization (PSO) algorithm called generalized particle swarm optimizer (GPSO). It extends the basic learning strategy of traditional PSO and exerts the swarms to significantly improve the group learning performance. In this scheme, a particle of PSO in each dimension does not only follow its own local optima, but also follows other superior particles'...
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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