American Journal of Information Science and Computer Engineering
Articles Information
American Journal of Information Science and Computer Engineering, Vol.3, No.1, Jan. 2017, Pub. Date: Jan. 21, 2017
Infrasonic Signals Clustering Based on Hilbert-Huang Transform and K-Means
Pages: 1-6 Views: 851 Downloads: 477
[01] Xuanchicheng Luo, School of Infomation Engineering, China University of Geosciences, Beijing, China.
[02] Shuqing Ming, School of Infomation Engineering, China University of Geosciences, Beijing, China.
[03] Mei Li, School of Infomation Engineering, China University of Geosciences, Beijing, China.
[04] Wei Tang, Comprehensive Nuclear-Test-Ban Treaty Beijing National Data Center, Beijing, China.
Because of the diversity of infrasound signals, it is difficult to classify different infrasound signals accurately. The different types of infrasound have different characteristics value in energy spectrum, therefore, this study obtained energy spectrum from which can extract the multi-dimensional feature vectors through the Hilbert-Huang transform (HHT) to distinguish different categories of infrasound signals. And then using the K-means algorithm to cluster multi-dimensional feature vectors, which has a good effect on solving the infrasound signal blind classification problem and increases the efficiency of signals clustering.
HHT, K-Means, Infrasound Signal, Cluster
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