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: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia
SIAM, Society for Industrial and Applied Mathematics
[2020]
|
| Schriftenreihe: | Computational science and engineering
22 |
| Schlagworte: | |
| 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: | Includes bibliographical references and index |
| Beschreibung: | xi, 341 Seiten |
| ISBN: | 9781611976113 |
Internformat
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| 245 | 1 | 0 | |a An introduction to compressed sensing |c M. Vidyasagar |
| 264 | 1 | |a Philadelphia |b SIAM, Society for Industrial and Applied Mathematics |c [2020] | |
| 300 | |a xi, 341 Seiten | ||
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| 490 | 1 | |a Computational science and engineering |v 22 | |
| 500 | |a Includes bibliographical references and index | ||
| 520 | 3 | |a 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 | |
| 653 | 0 | |a Signal processing | |
| 653 | 0 | |a Wavelets (Mathematics) | |
| 653 | 0 | |a Compressed sensing (Telecommunication) | |
| 653 | 0 | |a Linear programming | |
| 653 | 0 | |a Probability & statistics | |
| 653 | 0 | |a Combinatorics & graph theory | |
| 653 | 0 | |a Optimization | |
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| 653 | 0 | |a Compressed sensing (Telecommunication) | |
| 653 | 0 | |a Signal processing | |
| 653 | 0 | |a Wavelets (Mathematics) | |
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Datensatz im Suchindex
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| dewey-full | 621.382/2 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 621 - Applied physics |
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| dewey-search | 621.382/2 |
| dewey-sort | 3621.382 12 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
| format | Book |
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| id | DE-604.BV046347752 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:42:20Z |
| institution | BVB |
| isbn | 9781611976113 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031724315 |
| oclc_num | 1145197016 |
| open_access_boolean | |
| owner | DE-83 |
| owner_facet | DE-83 |
| physical | xi, 341 Seiten |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | SIAM, Society for Industrial and Applied Mathematics |
| record_format | marc |
| series | Computational science and engineering |
| series2 | Computational science and engineering |
| spelling | Vidyasagar, Mathukumalli 1947- (DE-588)124243584 aut An introduction to compressed sensing M. Vidyasagar Philadelphia SIAM, Society for Industrial and Applied Mathematics [2020] xi, 341 Seiten txt rdacontent n rdamedia nc rdacarrier Computational science and engineering 22 Includes bibliographical references and index 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 Online-Ausgabe 978-1-61197-612-0 Computational science and engineering 22 (DE-604)BV022382702 22 |
| 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 |
| volume_link | (DE-604)BV022382702 |
| work_keys_str_mv | AT vidyasagarmathukumalli anintroductiontocompressedsensing AT societyforindustrialandappliedmathematicspublisher anintroductiontocompressedsensing |