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Compressed sensing & sparse filtering
This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals...
| Autores principales: | , , |
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| Lenguaje: | eng |
| Publicado: |
Springer
2013
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1007/978-3-642-38398-4 http://cds.cern.ch/record/1625580 |
| _version_ | 1780933662368333824 |
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| author | Carmi, Avishy Y Mihaylova, Lyudmila S Godsill, Simon J |
| author_facet | Carmi, Avishy Y Mihaylova, Lyudmila S Godsill, Simon J |
| author_sort | Carmi, Avishy Y |
| collection | CERN |
| description | This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary. Apart from compressed sensing this book contains other related app |
| id | cern-1625580 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2013 |
| publisher | Springer |
| record_format | invenio |
| spelling | cern-16255802021-04-21T21:41:51Zdoi:10.1007/978-3-642-38398-4http://cds.cern.ch/record/1625580engCarmi, Avishy YMihaylova, Lyudmila SGodsill, Simon JCompressed sensing & sparse filteringEngineeringThis book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary. Apart from compressed sensing this book contains other related appSpringeroai:cds.cern.ch:16255802013 |
| spellingShingle | Engineering Carmi, Avishy Y Mihaylova, Lyudmila S Godsill, Simon J Compressed sensing & sparse filtering |
| title | Compressed sensing & sparse filtering |
| title_full | Compressed sensing & sparse filtering |
| title_fullStr | Compressed sensing & sparse filtering |
| title_full_unstemmed | Compressed sensing & sparse filtering |
| title_short | Compressed sensing & sparse filtering |
| title_sort | compressed sensing & sparse filtering |
| topic | Engineering |
| url | https://dx.doi.org/10.1007/978-3-642-38398-4 http://cds.cern.ch/record/1625580 |
| work_keys_str_mv | AT carmiavishyy compressedsensingsparsefiltering AT mihaylovalyudmilas compressedsensingsparsefiltering AT godsillsimonj compressedsensingsparsefiltering |