Volume 5, Issue 3, June 2016, Page: 37-41
Infrasound Source Identification Based on Spectral Moment Features
Zahra Madankan, Computer Engineering Department, Engineering Faculty, Alzahra University, Tehran, Iran
Noushin Riahi, Computer Engineering Department, Engineering Faculty, Alzahra University, Tehran, Iran
Akbar Ranjbar, Electronic Engineering Department, Engineering Faculty, Shahed University, Tehran, Iran
Received: Mar. 9, 2016;       Accepted: Apr. 5, 2016;       Published: Apr. 26, 2016
DOI: 10.11648/j.ijiis.20160503.11      View  4275      Downloads  173
Infrasound signals have a frequency range below the human hearing frequency range, and originate from different sources. Since these waves contain useful information about the occurrence of some important event, in this paper we intend to present a method for the recognition of sources of these signals. In the present paper, by using the feature spectral moment along with Mel-frequency cepstral coefficients (MFCC) and linear prediction coefficients (LPC) and also selecting a subset from the feature which plays a more discriminative role for the signal sources, and then by using classifier ensembles, we reached a 98.1% precision in the infrasound source identification.
Feature Extraction, Spectral Moment, Feature Selection, Recognition, Infrasound, Classifier Ensembles
To cite this article
Zahra Madankan, Noushin Riahi, Akbar Ranjbar, Infrasound Source Identification Based on Spectral Moment Features, International Journal of Intelligent Information Systems. Vol. 5, No. 3, 2016, pp. 37-41. doi: 10.11648/j.ijiis.20160503.11
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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