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Robust detection and pattern extraction of repeated signal components using subband shift-ACF

 
: Kurth, F.

:

Bestavros, A. ; Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society:
IEEE International Conference on Cloud Engineering, IC2E 2014. Proceedings : Boston, Massachusetts, 11-14th March 2014
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2014
ISBN: 978-1-4799-3766-0
ISBN: 978-1-4799-3768-4
S.520-525
International Conference on Cloud Engineering (IC2E) <2, 2014, Boston/Mass.>
International Workshop on Cloud Computing for Signal Processing, Coding, and Networking (IWCCSP) <1, 2014, Boston/Mass.>
Englisch
Konferenzbeitrag
Fraunhofer FKIE

Abstract
We propose a method for robustly detecting and extracting repeated signal components within a source signal. The method is based on the recently introduced shift autocorrelation (shift-ACF) which outperforms classical ACF in signal detection if a signal component is repeated more than once. In this paper, we extend shift-ACF to analyze the spectral structure of repeating signal components by using a subband decomposition. Subsequently, an algorithm for repeated event detection and extraction is proposed. An evaluation shows that the proposed subband shift-ACF outperforms detection based on classical cepstrum. We discuss several possible applications in the domain of sensor signal analysis, and particularly in audio monitoring.

: http://publica.fraunhofer.de/dokumente/N-360284.html