Minimum Complexity Pursuit for Universal Compressed Sensing
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سال
: 2014شناسه الکترونیک: 10.1109/TIT.2014.2302005
کلیدواژه(گان): compressed sensing,information theory,measurement errors,measurement uncertainty,Kolmogorov complexity,Occam razor,abstract algorithm,algorithmic information theory,general abstract meanings,group sparsity,high-dimensional signals,leveraging,measurement noise,minimum complexity pursuit,nascent field,randomized samples,signal recovery,simple structured objects,universal algorithms,universal compressed sensing,Approximation algorithms,Complexity theory,Computers,Noise,Noise
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آمار بازدید
Minimum Complexity Pursuit for Universal Compressed Sensing
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| contributor author | Jalali, Shirin | |
| contributor author | Maleki, Ali | |
| contributor author | Baraniuk, R.G. | |
| date accessioned | 2020-03-12T18:42:12Z | |
| date available | 2020-03-12T18:42:12Z | |
| date issued | 2014 | |
| identifier issn | 0018-9448 | |
| identifier other | 6719502.pdf | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/967439?locale-attribute=fa | |
| format | general | |
| language | English | |
| publisher | IEEE | |
| title | Minimum Complexity Pursuit for Universal Compressed Sensing | |
| type | Journal Paper | |
| contenttype | Metadata Only | |
| identifier padid | 8001427 | |
| subject keywords | compressed sensing | |
| subject keywords | information theory | |
| subject keywords | measurement errors | |
| subject keywords | measurement uncertainty | |
| subject keywords | Kolmogorov complexity | |
| subject keywords | Occam razor | |
| subject keywords | abstract algorithm | |
| subject keywords | algorithmic information theory | |
| subject keywords | general abstract meanings | |
| subject keywords | group sparsity | |
| subject keywords | high-dimensional signals | |
| subject keywords | leveraging | |
| subject keywords | measurement noise | |
| subject keywords | minimum complexity pursuit | |
| subject keywords | nascent field | |
| subject keywords | randomized samples | |
| subject keywords | signal recovery | |
| subject keywords | simple structured objects | |
| subject keywords | universal algorithms | |
| subject keywords | universal compressed sensing | |
| subject keywords | Approximation algorithms | |
| subject keywords | Complexity theory | |
| subject keywords | Computers | |
| subject keywords | Noise | |
| subject keywords | Noise | |
| identifier doi | 10.1109/TIT.2014.2302005 | |
| journal title | Information Theory, IEEE Transactions on | |
| journal volume | 60 | |
| journal issue | 4 | |
| filesize | 603722 | |
| citations | 0 |