Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its Applications

<p/> <p>The number of waveforms monitored in power systems is increasing rapidly. This creates a demand for computational tools that aid in the analysis of the phenomena and also that allow efficient transmission and storage of the information acquired. In this context, signal processing...

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Main Authors: Tcheou Michel P, da Silva Eduardo AB, Diniz Paulo SR, Rodrigues Marco AM, Lovisolo Lisandro
Format: Article
Language:English
Published: SpringerOpen 2007-01-01
Series:EURASIP Journal on Advances in Signal Processing
Online Access:http://asp.eurasipjournals.com/content/2007/029507
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spelling doaj-3d7668f4aa3343e3a6f95e23bcd9d0fa2020-11-25T00:26:35ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802007-01-0120071029507Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its ApplicationsTcheou Michel Pda Silva Eduardo ABDiniz Paulo SRRodrigues Marco AMLovisolo Lisandro<p/> <p>The number of waveforms monitored in power systems is increasing rapidly. This creates a demand for computational tools that aid in the analysis of the phenomena and also that allow efficient transmission and storage of the information acquired. In this context, signal processing techniques play a fundamental role. This work is a tutorial reviewing the principles and applications of atomic signal modeling of electric disturbance signals. The disturbance signal is modeled using a linear combination of damped sinusoidal components which are closely related to the phenomena typically observed in power systems. The signal model obtained is then employed for disturbance signal denoising, filtering of "DC components," and compression.</p> http://asp.eurasipjournals.com/content/2007/029507
collection DOAJ
language English
format Article
sources DOAJ
author Tcheou Michel P
da Silva Eduardo AB
Diniz Paulo SR
Rodrigues Marco AM
Lovisolo Lisandro
spellingShingle Tcheou Michel P
da Silva Eduardo AB
Diniz Paulo SR
Rodrigues Marco AM
Lovisolo Lisandro
Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its Applications
EURASIP Journal on Advances in Signal Processing
author_facet Tcheou Michel P
da Silva Eduardo AB
Diniz Paulo SR
Rodrigues Marco AM
Lovisolo Lisandro
author_sort Tcheou Michel P
title Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its Applications
title_short Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its Applications
title_full Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its Applications
title_fullStr Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its Applications
title_full_unstemmed Modeling of Electric Disturbance Signals Using Damped Sinusoids via Atomic Decompositions and Its Applications
title_sort modeling of electric disturbance signals using damped sinusoids via atomic decompositions and its applications
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2007-01-01
description <p/> <p>The number of waveforms monitored in power systems is increasing rapidly. This creates a demand for computational tools that aid in the analysis of the phenomena and also that allow efficient transmission and storage of the information acquired. In this context, signal processing techniques play a fundamental role. This work is a tutorial reviewing the principles and applications of atomic signal modeling of electric disturbance signals. The disturbance signal is modeled using a linear combination of damped sinusoidal components which are closely related to the phenomena typically observed in power systems. The signal model obtained is then employed for disturbance signal denoising, filtering of "DC components," and compression.</p>
url http://asp.eurasipjournals.com/content/2007/029507
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