dc.contributor.author |
Karagiannis, A |
en |
dc.contributor.author |
Constantinou, P |
en |
dc.date.accessioned |
2014-03-01T02:47:19Z |
|
dc.date.available |
2014-03-01T02:47:19Z |
|
dc.date.issued |
2011 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/33071 |
|
dc.subject |
Biomedical signal processing |
en |
dc.subject |
Computation Time Modeling |
en |
dc.subject |
Electrocardiography |
en |
dc.subject |
Empirical Mode Decomposition |
en |
dc.subject.other |
A-priori estimates |
en |
dc.subject.other |
Biomedical signal processing |
en |
dc.subject.other |
Computation time |
en |
dc.subject.other |
Computation Time Modeling |
en |
dc.subject.other |
Empirical Mode Decomposition |
en |
dc.subject.other |
Intrinsic mode functions |
en |
dc.subject.other |
Number of iterations |
en |
dc.subject.other |
Preprocessing techniques |
en |
dc.subject.other |
Resource allocation and management |
en |
dc.subject.other |
Signal processing technique |
en |
dc.subject.other |
Single variable |
en |
dc.subject.other |
Time scheduling |
en |
dc.subject.other |
Digital signal processing |
en |
dc.subject.other |
Electrocardiography |
en |
dc.subject.other |
Embedded systems |
en |
dc.subject.other |
Scheduling |
en |
dc.subject.other |
Computer resource management |
en |
dc.title |
Computation time study in biomedical signal processing with empirical mode decomposition: The case of electrocardiogram |
en |
heal.type |
conferenceItem |
en |
heal.identifier.primary |
10.1109/ICDSP.2011.6004965 |
en |
heal.identifier.secondary |
6004965 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/ICDSP.2011.6004965 |
en |
heal.publicationDate |
2011 |
en |
heal.abstract |
In this paper, a study of the Empirical Mode Decomposition (EMD) performance is presented in terms of computation time. Smart resource allocation and management in embedded systems are facilitated by signal processing techniques modeling for time scheduling of tasks. Empirical Mode Decomposition computation time is mainly determined by the number of iterations and the size of Intrinsic Mode Functions (IMF) set which are unknown at the beginning of the process. A metric is introduced to include these factors into a single variable of a linear model developed to a priori estimate method's computation time. In the same framework of Empirical Mode Decomposition computation time study the effects of noisy components and the application of preprocessing techniques are evaluated. © 2011 IEEE. |
en |
heal.journalName |
17th DSP 2011 International Conference on Digital Signal Processing, Proceedings |
en |
dc.identifier.doi |
10.1109/ICDSP.2011.6004965 |
en |