An introduction to compressed sensing:
Mathematical preliminaries -- Compressed sensing : problem formulations -- Null space--based conditions -- Concepts from graph theory -- Deterministic construction of measurement matrices -- Probabilistic construction of measurement matrices -- Matrix recovery and completion -- Some recent approache...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia, Pennsylvania
SIAM, Society for Industrial and Applied Mathematics
[2019]
|
| Schriftenreihe: | Computational science and engineering
22 |
| Schlagworte: | |
| Online-Zugang: | DE-91 DE-20 DE-706 DE-29 URL des Erstveröffentlichers |
| Zusammenfassung: | Mathematical preliminaries -- Compressed sensing : problem formulations -- Null space--based conditions -- Concepts from graph theory -- Deterministic construction of measurement matrices -- Probabilistic construction of measurement matrices -- Matrix recovery and completion -- Some recent approaches to vector recovery -- Optimization algorithms -- Case studies |
| Beschreibung: | 1 Online-Ressource (xi, 341 Seiten) |
| ISBN: | 9781611976120 |
| DOI: | 10.1137/1.9781611976120 |
Internformat
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| spelling | Vidyasagar, Mathukumalli 1947- (DE-588)124243584 aut An introduction to compressed sensing M. Vidyasagar Philadelphia, Pennsylvania SIAM, Society for Industrial and Applied Mathematics [2019] 1 Online-Ressource (xi, 341 Seiten) txt rdacontent c rdamedia cr rdacarrier Computational science and engineering 22 Mathematical preliminaries -- Compressed sensing : problem formulations -- Null space--based conditions -- Concepts from graph theory -- Deterministic construction of measurement matrices -- Probabilistic construction of measurement matrices -- Matrix recovery and completion -- Some recent approaches to vector recovery -- Optimization algorithms -- Case studies Signal processing Wavelets (Mathematics) Compressed sensing (Telecommunication) Linear programming Probability & statistics Combinatorics & graph theory Optimization TECHNOLOGY & ENGINEERING / Signals & Signal Processing MATHEMATICS / Linear & Nonlinear Programming MATHEMATICS / Probability & Statistics / General TECHNOLOGY & ENGINEERING / Imaging Systems Society for Industrial and Applied Mathematicspublisher pbl Erscheint auch als Druckausgabe 978-1-61197-611-3 Computational science and engineering 22 (DE-604)BV040633113 22 https://doi.org/10.1137/1.9781611976120 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Vidyasagar, Mathukumalli 1947- An introduction to compressed sensing Computational science and engineering |
| title | An introduction to compressed sensing |
| title_auth | An introduction to compressed sensing |
| title_exact_search | An introduction to compressed sensing |
| title_full | An introduction to compressed sensing M. Vidyasagar |
| title_fullStr | An introduction to compressed sensing M. Vidyasagar |
| title_full_unstemmed | An introduction to compressed sensing M. Vidyasagar |
| title_short | An introduction to compressed sensing |
| title_sort | an introduction to compressed sensing |
| url | https://doi.org/10.1137/1.9781611976120 |
| volume_link | (DE-604)BV040633113 |
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