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Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding

In this article, we make a comparative study for a new approach compression between discrete cosine transform (DCT) and discrete wavelet transform (DWT). We seek the transform proper to vector quantization to compress the EMG signals. To do this, we initially associated vector quantization and DCT,...

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Detalles Bibliográficos
Autores principales: Ntsama, Eloundou Pascal, Colince, Welba, Ele, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4829571/
https://www.ncbi.nlm.nih.gov/pubmed/27104132
http://dx.doi.org/10.1186/s40064-016-2095-7
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author Ntsama, Eloundou Pascal
Colince, Welba
Ele, Pierre
author_facet Ntsama, Eloundou Pascal
Colince, Welba
Ele, Pierre
author_sort Ntsama, Eloundou Pascal
collection PubMed
description In this article, we make a comparative study for a new approach compression between discrete cosine transform (DCT) and discrete wavelet transform (DWT). We seek the transform proper to vector quantization to compress the EMG signals. To do this, we initially associated vector quantization and DCT, then vector quantization and DWT. The coding phase is made by the SPIHT coding (set partitioning in hierarchical trees coding) associated with the arithmetic coding. The method is demonstrated and evaluated on actual EMG data. Objective performance evaluations metrics are presented: compression factor, percentage root mean square difference and signal to noise ratio. The results show that method based on the DWT is more efficient than the method based on the DCT.
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spelling pubmed-48295712016-04-21 Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding Ntsama, Eloundou Pascal Colince, Welba Ele, Pierre Springerplus Research In this article, we make a comparative study for a new approach compression between discrete cosine transform (DCT) and discrete wavelet transform (DWT). We seek the transform proper to vector quantization to compress the EMG signals. To do this, we initially associated vector quantization and DCT, then vector quantization and DWT. The coding phase is made by the SPIHT coding (set partitioning in hierarchical trees coding) associated with the arithmetic coding. The method is demonstrated and evaluated on actual EMG data. Objective performance evaluations metrics are presented: compression factor, percentage root mean square difference and signal to noise ratio. The results show that method based on the DWT is more efficient than the method based on the DCT. Springer International Publishing 2016-04-12 /pmc/articles/PMC4829571/ /pubmed/27104132 http://dx.doi.org/10.1186/s40064-016-2095-7 Text en © Ntsama et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Ntsama, Eloundou Pascal
Colince, Welba
Ele, Pierre
Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding
title Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding
title_full Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding
title_fullStr Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding
title_full_unstemmed Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding
title_short Comparison study of EMG signals compression by methods transform using vector quantization, SPIHT and arithmetic coding
title_sort comparison study of emg signals compression by methods transform using vector quantization, spiht and arithmetic coding
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4829571/
https://www.ncbi.nlm.nih.gov/pubmed/27104132
http://dx.doi.org/10.1186/s40064-016-2095-7
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