基于自适应模糊C-均值算法信号调制的识别

Modulation Identification of Signals Based on the Adaptive Fuzzy C-means

提出一种在加性白噪声错误的情况下的关于MFSK、MPSK和MASK调制识别算法。所述的这种分类技术使用瞬间频率、相位或幅度作为识别特征,利用模糊C-mean聚类算法中的有效性指标动态地调整聚类数目,实现对瞬时频率、相位或幅度的正确归类。仿真结果验证了此算法的可行性。

This paper proposes a new modulation identification fo r MFSK and MPSK and MASK on AWGN channel ,which takes the parameters such as the instantaneous frequencies or phases or amplitudes as identification features and uses the Adaptive Fuzzy C- mean Clustering algorithm to adjust the number of c lusters through the validity index . Simulation results show it feasible for cor rectly identifying the digital signals.