Fast and efficient signals recovery for deterministic compressive sensing: Applications to biosignals - Université de Lorraine Access content directly
Conference Papers Year : 2016

Fast and efficient signals recovery for deterministic compressive sensing: Applications to biosignals

Andrianiaina Ravelomanantsoa
  • Function : Author
  • PersonId : 779604
  • IdRef : 190137711
Hassan Rabah
Amar Rouane
  • Function : Author

Abstract

Compressed sensing is a technique that is suitable for compressing and recovering signals having sparse representations in certain bases. Compressed sensing has been widely used to optimize the measurement process of power and bandwidth constrained systems like wireless body sensor network. The central issues with compressed sensing are mainly the construction of measurement matrices and the development of efficient recovery algorithms. In this paper, we proposed a simple and fast recovery algorithm which performed a thresholding in the discrete cosine transform domain. We validated it by recovering electrocardiogram and electromyogram signals taken from the Phyiobank database. The simulation and experimental results have shown that the proposed recovery algorithm was 25 and 12 times faster than orthogonal matching pursuit and stagewise orthogonal matching pursuit, respectively. In addition, depending on the compression ratio, the signal-to-noise ratio of recovered signals were improved up to 2 dB.
No file

Dates and versions

hal-03982547 , version 1 (10-02-2023)

Identifiers

Cite

Andrianiaina Ravelomanantsoa, Hassan Rabah, Amar Rouane. Fast and efficient signals recovery for deterministic compressive sensing: Applications to biosignals. 2015 Conference on Design and Architectures for Signal and Image Processing (DASIP), Sep 2015, Krakow, Poland. pp.136-141, ⟨10.1109/DASIP.2015.7367263⟩. ⟨hal-03982547⟩
41 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More