@article {880,
	title = {Spectrum Skeletonization: A New Method for Acoustic Signal Feature Extraction.},
	journal = {ACTA CYBERNETICA-SZEGED},
	volume = {21},
	year = {2013},
	note = {$\#$Szerz{\H o} vagy Forr{\'a}skiad{\'a}s k{\'e}sz{\'\i}t{\H o}je vagy Kritikai kiad{\'a}s k{\'e}sz{\'\i}t{\H o}je ismeretlen},
	month = {2013},
	pages = {89 - 103},
	publisher = {University of Szeged, Institute of Informatics},
	type = {Journal article},
	address = {Szeged},
	abstract = {<p>Vibration Analysis Tests (VAT) and Acoustic Emission tests (AE) are used in several industrial applications. Many of them perform analysis in the frequency domain. Peaks in the power density spectrum hold relevant information about acoustic events. In this paper we propose a novel method for feature extraction of vibration samples by analyzing the shape of their auto power spectrum density function. The approach uses skeletonization techniques in order to find the hierarchical structure of the spectral peaks. The proposed method can be applied as a preprocessing step for spectrum analysis of vibration signals. <tt> </tt></p>},
	isbn = {0324-721X},
	author = {Tibor Dobj{\'a}n and G{\'a}bor N{\'e}meth}
}
