A Signal Sorting Algorithm Based on LOF De-Noised Clustering

Abstract

In this paper, an algorithm for removing outliers is proposed for low SNR signals. Firstly, the coarse separation of signals is performed by using the isolated point removal algorithm based on Euclidean distance, and then the coarsely separated data is finely separated by the LOF algorithm based on density detection. The remaining signal data after fine separation is clustered. Through simulation analysis, the algorithm can remove all isolated points at the cost of useful signal loss at low SNR, and the residual signal clustering effect is better.