| 000 | 02865nam a2200469Ii 4500 | ||
|---|---|---|---|
| 001 | 9781351261364 | ||
| 003 | FlBoTFG | ||
| 005 | 20220711212240.0 | ||
| 006 | m o d | ||
| 007 | cr | ||
| 008 | 190122t20182019fluab ob 001 0 eng d | ||
| 020 | _a9781351261364(e-book : PDF) | ||
| 035 | _a(OCoLC)1076269164 | ||
| 040 |
_aFlBoTFG _cFlBoTFG _erda |
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| 050 | 4 | _aTA1638 | |
| 072 | 7 |
_aTEC _x007000 _2bisacsh |
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| 072 | 7 |
_aTJK _2bicscc |
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| 100 | 1 |
_aMajumdar, Angshul, _eauthor. _914708 |
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| 245 | 1 | 0 |
_aCompressed Sensing for Engineers / _cby Angshul Majumdar. |
| 250 | _aFirst edition. | ||
| 264 | 1 |
_aBoca Raton, FL : _bCRC Press, _c[2018]. |
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| 264 | 4 | _c©2019. | |
| 300 |
_a1 online resource (292 pages) : _b32 illustrations, text file, PDF. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_acomputer _2rdamedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 490 | 1 | _aDevices, Circuits, and Systems | |
| 504 | _aIncludes bibliographical references and index. | ||
| 505 | 0 | 0 | _tIntroduction. Greedy Algorithms. Sparse Recovery. Co-sparse Recovery. Group Sparsity. Joint Sparsity. Low-rank Matrix Recovery. Combined Sparse and Low-rank Recovery. Dictionary Learning. Medical Imaging. Biomedical Signal Reconstruction. Regression. Classification. Computational Imaging. Denoising. |
| 520 | 3 | _aCompressed Sensing (CS) in theory deals with the problem of recovering a sparse signal from an under-determined system of linear equations. The topic is of immense practical significance since all naturally occurring signals can be sparsely represented in some domain. In recent years, CS has helped reduce scan time in Magnetic Resonance Imaging (making scans more feasible for pediatric and geriatric subjects) andhas also helped reducethe health hazard in X-Ray Computed CT. This book is a valuable resourcesuitable for an engineering student in signal processing and requires a basic understanding of signal processing and linear algebra. Covers fundamental concepts of compressed sensing Makes subject matter accessible for engineers of various levels Focuses on algorithms including group-sparsity and row-sparsity, as well as applications to computational imaging, medical imaging, biomedical signal processing, and machine learning. Includes MATLAB examples for further development. | |
| 530 | _aAlso available in print format. | ||
| 650 | 0 |
_aCompressed sensing (Telecommunication) _94529 |
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| 650 | 0 |
_aImage processing _xDigital techniques. _94145 |
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| 650 | 0 |
_aImage compression. _913490 |
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| 650 | 0 |
_aSignal processing _xMathematics. _93827 |
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| 655 | 0 |
_aElectronic books. _93294 |
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| 710 | 2 |
_aTaylor and Francis. _910719 |
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| 776 | 0 | 8 |
_iPrint version: _z9780815365563 |
| 830 | 0 |
_aDevices, Circuits, and Systems. _912115 |
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| 856 | 4 | 0 |
_uhttps://www.taylorfrancis.com/books/9781351261364 _zClick here to view |
| 942 | _cEBK | ||
| 999 |
_c70771 _d70771 |
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