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• W2141162783 abstract "In this paper, synthesis of unequally spaced linear antenna arrays based on an inheritance learning particle swarm optimization (ILPSO) is presented. In order to improve the optimization e-ciency of the PSO algorithm, we propose an inheritance learning strategy that can be applied to difierent topology of difierent PSO algorithms. In ILPSO algorithm, each cycle contains several PSO optimization processes, and uniform initial particle positions, part of which inherited from the good results in pre-cycles, are adopted in post-cycles. ILPSO enhances the exploration ability of PSO algorithm signiflcantly, and can escape from the trap of local optimum areas with greater probability. The results demonstrate good performance of the ILPSO in solving a set of eight 30-D benchmark functions when compared to nine other variants of the PSO. The novel proposed algorithm has been applied in 32-element position-only array synthesis with three difierent constraints, simulation results show that ILPSO obtains better synthesis results reliably and e-ciently." @default.
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• W2141162783 date "2011-01-01" @default.
• W2141162783 modified "2023-10-15" @default.
• W2141162783 title "SYNTHESIS OF UNEQUALLY SPACED ANTENNA ARRAYS BY USING INHERITANCE LEARNING PARTICLE SWARM OPTIMIZATION" @default.
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• W2141162783 doi "https://doi.org/10.2528/pier11050502" @default.
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