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- W2098985750 abstract "This paper introduces a novel approach for the optimization of large-N fractal random antenna arrays using genetic algorithms. Genetic algorithms often become overwhelmed by large numbers of input parameters, leading to an inefficient optimization processes. Fractal-random geometries lend themselves well to genetic algorithm optimization through the ability to describe their complex array structures with only a small number of input parameters. In addition, the recursive properties of fractal-random arrays allow for the rapid calculation of the array factor, which can be exploited to significantly speed up the convergence of the GA. This paper describes a method that increases the number of generators used to construct the array as the optimization progresses, maximizing the benefit of using fractal-random geometries to describe large-N arrays. Several optimized solutions are discussed, the largest being a 1650 element linear fractal-random array with a -23.57 dB side-lobe level and a beamwidth of 0.05/spl deg/." @default.
- W2098985750 created "2016-06-24" @default.
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- W2098985750 date "2005-06-07" @default.
- W2098985750 modified "2023-09-25" @default.
- W2098985750 title "The autopolyploidy enhanced evolution of large-N fractal-random arrays" @default.
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- W2098985750 doi "https://doi.org/10.1109/radar.2005.1435959" @default.
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