dc.contributor.author |
Thanasopoulos, IA |
en |
dc.contributor.author |
Avaritsiotis, JN |
en |
dc.date.accessioned |
2014-03-01T02:45:47Z |
|
dc.date.available |
2014-03-01T02:45:47Z |
|
dc.date.issued |
2008 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/32386 |
|
dc.subject |
a priori knowledge |
en |
dc.subject |
Computational Complexity |
en |
dc.subject |
Computer Program |
en |
dc.subject |
Discrete Wavelet Transform |
en |
dc.subject |
Event Detection |
en |
dc.subject |
Haar Wavelet |
en |
dc.subject |
Haar Wavelet Transform |
en |
dc.subject |
Seismic Waves |
en |
dc.subject |
Sensor Network |
en |
dc.subject |
Source Localization |
en |
dc.subject |
Time of Arrival |
en |
dc.subject |
Time Domain |
en |
dc.subject.other |
Acoustic microscopes |
en |
dc.subject.other |
Amplitude modulation |
en |
dc.subject.other |
Chemical sensors |
en |
dc.subject.other |
Chlorine compounds |
en |
dc.subject.other |
Computational complexity |
en |
dc.subject.other |
Discrete wavelet transforms |
en |
dc.subject.other |
Electric fault currents |
en |
dc.subject.other |
Estimation |
en |
dc.subject.other |
Feature extraction |
en |
dc.subject.other |
Method of moments |
en |
dc.subject.other |
Missile bases |
en |
dc.subject.other |
Seismic waves |
en |
dc.subject.other |
Seismology |
en |
dc.subject.other |
Sensor arrays |
en |
dc.subject.other |
Sensor networks |
en |
dc.subject.other |
Sensors |
en |
dc.subject.other |
Signal processing |
en |
dc.subject.other |
Wavelet transforms |
en |
dc.subject.other |
A-priori |
en |
dc.subject.other |
Computer programs |
en |
dc.subject.other |
Discrete-wavelet-transform |
en |
dc.subject.other |
Event detection |
en |
dc.subject.other |
Extraction of information |
en |
dc.subject.other |
Haar wavelet transforms |
en |
dc.subject.other |
HAAR wavelets |
en |
dc.subject.other |
Multichannel signal processing |
en |
dc.subject.other |
Noisy environments |
en |
dc.subject.other |
Seismic detection |
en |
dc.subject.other |
Seismic signals |
en |
dc.subject.other |
Simulation results |
en |
dc.subject.other |
Source localization |
en |
dc.subject.other |
Spectral characteristics |
en |
dc.subject.other |
Time domain OCT |
en |
dc.subject.other |
Time domains |
en |
dc.subject.other |
Time-of-arrival |
en |
dc.subject.other |
Time-of-arrival estimation |
en |
dc.subject.other |
Transient signals |
en |
dc.subject.other |
Time domain analysis |
en |
dc.title |
Seismic detection and time of arrival estimation in noisy environments based on the haar wavelet transform |
en |
heal.type |
conferenceItem |
en |
heal.identifier.primary |
10.1109/SAM.2008.4606906 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/SAM.2008.4606906 |
en |
heal.identifier.secondary |
4606906 |
en |
heal.publicationDate |
2008 |
en |
heal.abstract |
In this paper we propose a discrete wavelet transform (DWT) method for event detection and estimation of the time of arrival (TOA) of seismic signals in a sensor network. The Haar wavelet is selected for its low computational complexity and its good locality in time domain which is essential for the analysis of transient signals. The proposed method requires no a priori knowledge about the spectral characteristics of the signals, because the algorithm defines the optimum scales for the extraction of information by time-domain features as the signal is acquired. The performance of the algorithm is verified using a computer program that simulates the propagation of surface seismic waves. Simulation results corroborate the suitability of the proposed method for source localization applications. © 2008 IEEE. |
en |
heal.journalName |
SAM 2008 - 5th IEEE Sensor Array and Multichannel Signal Processing Workshop |
en |
dc.identifier.doi |
10.1109/SAM.2008.4606906 |
en |
dc.identifier.spage |
433 |
en |
dc.identifier.epage |
436 |
en |