Abstract
Abstract—Mind Evolutionary Algorithm (MEA) uses ‘similar taxis’ operation and ‘dissimilation’ operation by imitating the human mind evolution to processes numerical optimization, overcoming the prematurity and improving searching efficiency. Given the determinate number and space between the antenna arrays units, the feeding-back amplitudes and phases are optimized and selected by this way to make the shaped-beam patterns satisfy the designing request. Computer simulations show that Mind Evolutionary Algorithm can be applied in optimization problems of uniformly-spaced linear array and the optimization result is better than that obtained from Genetic Algorithm.
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