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http://dx.doi.org/10.5762/KAIS.2010.11.3.978

Target Feature Extraction using Wavelet Coefficient for Acoustic Target Classification in Wireless Sensor Network  

Cha, Dae-Hyun (Dept of Electric Electronic Computer, Kyungpook National University)
Lee, Tae-Young (Dept of Electric Electronic Computer, Kyungpook National University)
Hong, Jin-Keung (Dept of Information Communication, Baekseok University)
Han, Kun-Hee (Dept of Information Communication, Baekseok University)
Hwang, Chan-Sik (Dept of Electric Electronic Computer, Kyungpook National University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.11, no.3, 2010 , pp. 978-983 More about this Journal
Abstract
Acoustic target classification in wireless sensor network is important research at environmental surveillance, invasion surveillance, multiple target separation. General sensor node signal processing methods concentrated on received signal energy based target detection and received raw signal compression. The former is not suited to target classification because of almost every target information are lost except target energy. The latter bring down life-time of sensor node owing to high computational complexity and transmission energy. In this paper, we introduce an feature extraction algorithm for acoustic target classification in wireless sensor network which has time and frequency information. The proposed method extracts time information and de-noised target classification information using wavelet decomposition step. This method reduces communication energy by 28% of original signal and computational complexity.
Keywords
Wireless Sensor Network; Wavelet; Feature Extraction;
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