Compressive sensing: A methodological approach to an efficient signal processing
Compressive Sensing (CS) is a new paradigm for signal acquisition and processing, which integrates sampling, compression, dimensionality reduction and optimization, which has caught the attention of a many researchers; SC allows the reconstruction of dispersed signals in a given domain from a set of...
- Autores:
-
Astaiza Hoyos, Evelio
Jojoa Gómez, Pablo Emilio
Bermúdez Orozco, Héctor Fabio
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2015
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/60675
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/60675
http://bdigital.unal.edu.co/59007/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
Compressive Sensing
Sampling
Compression
Optimization
Signal Processing
Methodology
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | Compressive Sensing (CS) is a new paradigm for signal acquisition and processing, which integrates sampling, compression, dimensionality reduction and optimization, which has caught the attention of a many researchers; SC allows the reconstruction of dispersed signals in a given domain from a set of measurements could be described as incomplete, due to that the rate at which the signal is sampled is much smaller than Nyquist's rate. This article presents an approach to address methodological issues in the field of processing signals from the perspective of SC. |
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