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首页> 外文期刊>International Journal of Engineering Research and Applications >Reduction of Side Lobe Levels of Sum Patterns from Discrete Arrays Using Genetic Algorithm
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Reduction of Side Lobe Levels of Sum Patterns from Discrete Arrays Using Genetic Algorithm

机译:使用遗传算法降低离散阵列中和模式的旁瓣水平

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Antennas are vital elements in any wireless communication systems. Radiation pattern is an important characteristic of an antenna. Radiation pattern of a single antenna element is fixed. Required radiation patterns can be generated from array of antennas. Different pattern synthesis techniques are reported in the literature. Generated patterns from selected pattern synthesis techniques can further be optimized using optimization techniques like genetic algorithms. Genetic Algorithm(GA) is a popular optimization technique for better solutions. A typical genetic algorithm requires genetic representation of the solution domain, fitness function to evaluate the solution domain. Once the genetic representation and the fitness function are defined, a GA proceeds to initialize a population of solutions and then to improve it through repetitive application of the mutation, crossover, inversion and selection operators. Sum patterns are generated using Fourier synthesis technique. The task of reducing the side lobe levels of generated sum patterns using optimi zation technique is considered in this work
机译:在任何无线通信系统中,天线都是至关重要的元素。辐射方向图是天线的重要特征。单个天线元件的辐射方向图是固定的。可以从天线阵列生成所需的辐射图。文献报道了不同的​​图案合成技术。可以使用诸如遗传算法之类的优化技术进一步优化从选定的模式合成技术生成的模式。遗传算法(GA)是一种流行的优化技术,可以提供更好的解决方案。典型的遗传算法需要解域的遗传表示,适应度函数来评估解域。一旦定义了遗传表示和适应度函数,GA便会初始化一组解决方案,然后通过重复应用突变,交叉,倒置和选择算子来对其进行改进。使用傅立叶合成技术生成求和模式。在这项工作中考虑了使用优化技术降低生成的和模式的旁瓣水平的任务

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