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Data Compression and Compressed Sensing in Imaging Mass Spectrometry and Sporadic Communication
Annotation
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin :
Logos Verlag Berlin,
2014.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
| LEADER | 00000cam a2200000Mu 4500 | ||
|---|---|---|---|
| 001 | EBOOKCENTRAL_on1112421877 | ||
| 003 | OCoLC | ||
| 005 | 20240329122006.0 | ||
| 006 | m o d | ||
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| 008 | 190817s2014 gw o 000 0 eng d | ||
| 040 | |a EBLCP |b eng |e pn |c EBLCP |d YDX |d OCLCQ |d REDDC |d OCLCO |d UX1 |d OCLCF |d SFB |d OCLCO |d OCLCQ |d OCLCO |d OCLCL | ||
| 019 | |a 1038392568 |a 1290086288 | ||
| 020 | |a 9783832591663 | ||
| 020 | |a 3832591664 | ||
| 020 | |z 383253850X | ||
| 020 | |z 9783832538507 | ||
| 029 | 1 | |a AU@ |b 000067961761 | |
| 035 | |a (OCoLC)1112421877 |z (OCoLC)1038392568 |z (OCoLC)1290086288 | ||
| 050 | 4 | |a QD96.M3 |b .B378 2014 | |
| 082 | 0 | 4 | |a 543.0873 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Bartels, Andreas. | |
| 245 | 1 | 0 | |a Data Compression and Compressed Sensing in Imaging Mass Spectrometry and Sporadic Communication |
| 260 | |a Berlin : |b Logos Verlag Berlin, |c 2014. | ||
| 300 | |a 1 online resource (192 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Intro; 1 Introduction; 1.1 The big data problem; 1.2 Data compression; 1.3 What compressed sensing is about; 1.4 Scientific contributions of the thesis; 1.5 Organization of the thesis; 2 Preliminaries and concepts; 2.1 Notations; 2.2 Proximity operators and algorithms; 3 Data compression; 3.1 What is compression?; 3.2 Compression and quality measures; 3.3 Mathematical techniques; 3.3.1 `0 and `1 minimization; 3.3.2 TV minimization; 3.3.3 Nonnegative matrix factorization; 4 Compressed Sensing; 4.1 Introduction; 4.2 Uniqueness, sparseness and other properties; 4.2.1 Coherence | |
| 505 | 8 | |a 4.2.2 Restricted isometry property4.3 Stable `1 minimization; 4.4 Stable total variation minimization; 4.5 Coherent and redundant dictionaries; 4.6 Asymmetric restricted isometry property; 5 Imaging mass spectrometry in a nutshell; 5.1 Mass spectrometry; 5.2 Imaging mass spectrometry; 5.3 Datasets used in this thesis; 5.3.1 Rat brain; 5.3.2 Rat kidney; 6 Compression in imaging mass spectrometry; 6.1 Introduction; 6.2 Peak picking; 6.2.1 Spectral peak picking; 6.2.2 Spatial peak picking; 6.3 Denoising; 6.4 Nonnegative matrix factorization; 6.5 Conclusion | |
| 505 | 8 | |a 7 Compressed sensing in imaging mass spectrometry7.1 Introduction; 7.2 The compressed sensing process; 7.3 First assumption: compressible spectra; 7.4 Second assumption: sparse image gradients; 7.5 The final model; 7.6 Robust recovery; 7.7 Numerical results; 7.8 Conclusion; 8 Compressed sensing based multi-user detection; 8.1 Introduction; 8.2 Sporadic communication; 8.3 Multi-user system modelling; 8.4 The elastic-net; 8.5 The multi-user test setup; 8.6 A parameter choice rule: The C-curve criterion; 8.7 An offline approach; 8.8 Conclusion; 9 Conclusion | |
| 520 | 8 | |a Annotation |b This thesis contributes to the fields of data compression and compressed sensing and their application to imaging mass spectrometry and sporadic communication. Compressed sensing is mainly built on the knowledge that most data is compressible or sparse, meaning that most of its content is redundant and not worth being measured. As a main result in this work, a compressed sensing model for imaging mass spectrometry is introduced. It combines peak-picking of the spectra and denoising of the m/z-images A robustness result for the reconstruction of compressed measured data is presented which generalizes known reconstruction guarantees. | |
| 504 | |a Includes bibliographical references. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Mass spectrometry. | |
| 650 | 6 | |a Spectrométrie de masse. | |
| 650 | 7 | |a mass spectrometry. |2 aat | |
| 650 | 7 | |a Mass spectrometry |2 fast | |
| 758 | |i has work: |a Data Compression and Compressed Sensing in Imaging Mass Spectrometry and Sporadic Communication (Text) |1 https://id.oclc.org/worldcat/entity/E39PD3TvR3x96r3VRpQr3jKY8C |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Bartels, Andreas. |t Data Compression and Compressed Sensing in Imaging Mass Spectrometry and Sporadic Communication. |d Berlin : Logos Verlag Berlin, ©2014 |z 9783832538507 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5850430 |z Texto completo |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL5850430 | ||
| 938 | |a YBP Library Services |b YANK |n 15453939 | ||
| 994 | |a 92 |b IZTAP | ||