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A Signal Sorting Algorithm Based on LOF De-Noised Clustering

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationCommunications, Signal Processing, and Systems - Proceedings of the 8th International Conference on Communications, Signal Processing, and Systems, CSPS 2019
EditorsQilian Liang, Wei Wang, Xin Liu, Zhenyu Na, Min Jia, Baoju Zhang
PublisherSpringer
Pages268-275
Number of pages8
ISBN (Print)9789811394089
DOIs
StatePublished - 2020
Event8th International Conference on Communications, Signal Processing, and Systems, CSPS 2019 - Urumqi, China
Duration: 20 Jul 201922 Jul 2019

Publication series

NameLecture Notes in Electrical Engineering
Volume571 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference8th International Conference on Communications, Signal Processing, and Systems, CSPS 2019
Country/TerritoryChina
CityUrumqi
Period20/07/1922/07/19

Keywords

  • Clustering
  • LOF
  • Outlier removal

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