基于PCA及FCM的C波段无线电信号分类方法

摘要

提出了一种基于模糊C均值聚类分析以及主成分分析的无线电异常信号分类方法，该方法利用主成分分析对信号数据进行降维并通过模糊C均值对信号数据进行分类，对目前常用的通过专家经验进行信号特征选取的方法进行了改进。实验结果证明了该方法的有效性，能快速高效地判断异常信号的类别。%A C band radio signal classification algorithm is proposed based on the principal component analysis (PCA) and fuzzy C means algorithm (FCM). The dimensionality of cluster data were reduced by using the principal component analysis and the cluster data were classified by using fuzzy C means approach. The process of feature selection put forward by experts’ experience was improved. The experiment result proves that this method is more effective and the type of signal can be recognized faster.