Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations
Joint Authors
Stanković, Srdjan
Orović, Irena
Ioana, Cornel
Li, Xiumei
Papić, Vladan
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-10-25
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Compressive sensing has emerged as an area that opens new perspectives in signal acquisition and processing.
It appears as an alternative to the traditional sampling theory, endeavoring to reduce the required number of samples for successful signal reconstruction.
In practice, compressive sensing aims to provide saving in sensing resources, transmission, and storage capacities and to facilitate signal processing in the circumstances when certain data are unavailable.
To that end, compressive sensing relies on the mathematical algorithms solving the problem of data reconstruction from a greatly reduced number of measurements by exploring the properties of sparsity and incoherence.
Therefore, this concept includes the optimization procedures aiming to provide the sparsest solution in a suitable representation domain.
This work, therefore, offers a survey of the compressive sensing idea and prerequisites, together with the commonly used reconstruction methods.
Moreover, the compressive sensing problem formulation is considered in signal processing applications assuming some of the commonly used transformation domains, namely, the Fourier transform domain, the polynomial Fourier transform domain, Hermite transform domain, and combined time-frequency domain.
American Psychological Association (APA)
Orović, Irena& Papić, Vladan& Ioana, Cornel& Li, Xiumei& Stanković, Srdjan. 2016. Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1112591
Modern Language Association (MLA)
Orović, Irena…[et al.]. Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations. Mathematical Problems in Engineering No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1112591
American Medical Association (AMA)
Orović, Irena& Papić, Vladan& Ioana, Cornel& Li, Xiumei& Stanković, Srdjan. Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1112591
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112591