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An Optimized Resolution Coefficient Algorithm of Gray Relation Classifier

机译:灰色关系分类器优化分辨率系数算法

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Resolution coefficient of traditional gray relation classifier usually takes a fixed value of 0.5, which greatly limits the adaptive ability, and reduces the effectiveness of this algorithm to identify signals. To solve this problem, an improved optimized resolution coefficient algorithm of gray relation classifier was proposed. Particle swarm optimization (PSO) algorithm was used to calculate the optimized resolution coefficient corresponding to the best classification results under different SNR environment. The adaptive ability of this algorithm was improved by improving the selection method of resolution coefficient and ultimately the classification effect was improved. Simulation results show that, compared with the traditional improved algorithm, it can improve the recognition rate of signals under different SNR environment, and have a good application value.
机译:传统灰色关系分类器的分辨率系数通常需要0.5的固定值,这极大地限制了自适应能力,并降低了该算法识别信号的有效性。为了解决这个问题,提出了一种改进的灰色关系分类的优化分辨率系数算法。粒子群优化(PSO)算法用于计算与不同SNR环境下最佳分类结果对应的优化分辨率系数。通过改善分辨率系数的选择方法,最终改善了该算法的自适应能力,提高了分类效果。仿真结果表明,与传统的改进算法相比,它可以提高不同SNR环境下的信号识别率,并具有良好的应用价值。

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