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An Optimized Resolution Coefficient Algorithm of Gray Relation Classifier

机译:灰色关联分类器的最佳分辨率系数算法

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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:传统的灰色关联分类器的分辨率系数通常取固定值0.5,极大地限制了自适应能力,降低了该算法识别信号的效率。针对这一问题,提出了一种改进的灰度关联分类器的优化分辨率系数算法。采用粒子群算法(PSO)来计算与不同信噪比环境下最佳分类结果相对应的优化分辨率系数。通过改进分辨率系数的选择方法,提高了算法的自适应能力,最终提高了分类效果。仿真结果表明,与传统的改进算法相比,该算法在不同信噪比环境下可以提高信号的识别率,具有良好的应用价值。

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