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You searched for subject:( sparse sampling ). Showing records 1 – 30 of 4695 total matches.

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Université de Grenoble

1. Coppa, Bertrand. Sur quelques applications du codage parcimonieux et sa mise en oeuvre : On compressed sampling applications and its implementation.

Degree: Docteur es, Sciences et technologie industrielles, 2013, Université de Grenoble

Le codage parcimonieux permet la reconstruction d'un signal à partir de quelques projections linéaires de celui-ci, sous l'hypothèse que le signal se décompose de manière… (more)

Subjects/Keywords: Codage parcimonieux; Problème inverse; Minimisation L1; Sparse sampling; Compressed sampling; Inverse problem; L1-minimization

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Coppa, B. (2013). Sur quelques applications du codage parcimonieux et sa mise en oeuvre : On compressed sampling applications and its implementation. (Doctoral Dissertation). Université de Grenoble. Retrieved from http://www.theses.fr/2013GRENT009

Chicago Manual of Style (16th Edition):

Coppa, Bertrand. “Sur quelques applications du codage parcimonieux et sa mise en oeuvre : On compressed sampling applications and its implementation.” 2013. Doctoral Dissertation, Université de Grenoble. Accessed January 22, 2021. http://www.theses.fr/2013GRENT009.

MLA Handbook (7th Edition):

Coppa, Bertrand. “Sur quelques applications du codage parcimonieux et sa mise en oeuvre : On compressed sampling applications and its implementation.” 2013. Web. 22 Jan 2021.

Vancouver:

Coppa B. Sur quelques applications du codage parcimonieux et sa mise en oeuvre : On compressed sampling applications and its implementation. [Internet] [Doctoral dissertation]. Université de Grenoble; 2013. [cited 2021 Jan 22]. Available from: http://www.theses.fr/2013GRENT009.

Council of Science Editors:

Coppa B. Sur quelques applications du codage parcimonieux et sa mise en oeuvre : On compressed sampling applications and its implementation. [Doctoral Dissertation]. Université de Grenoble; 2013. Available from: http://www.theses.fr/2013GRENT009


Rochester Institute of Technology

2. Liu, Dengyu. Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging.

Degree: MS, Chester F. Carlson Center for Imaging Science (COS), 2015, Rochester Institute of Technology

  Cameras face a fundamental tradeoff between spatial and temporal resolution. Digital still cameras can capture images with high spatial resolution, but most high-speed video… (more)

Subjects/Keywords: Computational camera; Dictionary learning; Space-time sampling; Sparse reconstruction

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APA (6th Edition):

Liu, D. (2015). Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/8906

Chicago Manual of Style (16th Edition):

Liu, Dengyu. “Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging.” 2015. Masters Thesis, Rochester Institute of Technology. Accessed January 22, 2021. https://scholarworks.rit.edu/theses/8906.

MLA Handbook (7th Edition):

Liu, Dengyu. “Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging.” 2015. Web. 22 Jan 2021.

Vancouver:

Liu D. Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging. [Internet] [Masters thesis]. Rochester Institute of Technology; 2015. [cited 2021 Jan 22]. Available from: https://scholarworks.rit.edu/theses/8906.

Council of Science Editors:

Liu D. Efficient Space-Time Sampling with Pixel-wise Coded Exposure for High Speed Imaging. [Masters Thesis]. Rochester Institute of Technology; 2015. Available from: https://scholarworks.rit.edu/theses/8906


Penn State University

3. Wilson, Scott Alden. Compressive Microwave Radar Holography.

Degree: 2014, Penn State University

 Radar holography has been established as an effective image reconstruction process by which the measured diffraction pattern across an aperture provides information of a three-dimensional… (more)

Subjects/Keywords: Compressive sensing; sparse sampling; near-field imaging; radar imaging; microwave holography

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APA (6th Edition):

Wilson, S. A. (2014). Compressive Microwave Radar Holography. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/23274

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wilson, Scott Alden. “Compressive Microwave Radar Holography.” 2014. Thesis, Penn State University. Accessed January 22, 2021. https://submit-etda.libraries.psu.edu/catalog/23274.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wilson, Scott Alden. “Compressive Microwave Radar Holography.” 2014. Web. 22 Jan 2021.

Vancouver:

Wilson SA. Compressive Microwave Radar Holography. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Jan 22]. Available from: https://submit-etda.libraries.psu.edu/catalog/23274.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wilson SA. Compressive Microwave Radar Holography. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/23274

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


McMaster University

4. Chinta, Venkateswarao Yogesh. Sparse Sampling of Velocity MRI.

Degree: MASc, 2011, McMaster University

Standard MRI is used to image objects at rest. In addition to standard MRI images, which measure tissues at rest, Phase Contrast MRI can… (more)

Subjects/Keywords: Optimization; Velocity MRI; Sparse sampling; k-space; Computational Engineering; Computational Engineering

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APA (6th Edition):

Chinta, V. Y. (2011). Sparse Sampling of Velocity MRI. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/10439

Chicago Manual of Style (16th Edition):

Chinta, Venkateswarao Yogesh. “Sparse Sampling of Velocity MRI.” 2011. Masters Thesis, McMaster University. Accessed January 22, 2021. http://hdl.handle.net/11375/10439.

MLA Handbook (7th Edition):

Chinta, Venkateswarao Yogesh. “Sparse Sampling of Velocity MRI.” 2011. Web. 22 Jan 2021.

Vancouver:

Chinta VY. Sparse Sampling of Velocity MRI. [Internet] [Masters thesis]. McMaster University; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11375/10439.

Council of Science Editors:

Chinta VY. Sparse Sampling of Velocity MRI. [Masters Thesis]. McMaster University; 2011. Available from: http://hdl.handle.net/11375/10439

5. bi, xiaofei. Compressed Sampling for High Frequency Receivers Applications.

Degree: Mathematics and Natural Sciences, 2011, University of Gävle

  In digital signal processing field, for recovering the signal without distortion, Shannon sampling theory must be fulfilled in the traditional signal sampling. However, in… (more)

Subjects/Keywords: Compressive Sampling (CS); sparse representation; measurement matrix; signal reconstruction.

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APA (6th Edition):

bi, x. (2011). Compressed Sampling for High Frequency Receivers Applications. (Thesis). University of Gävle. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

bi, xiaofei. “Compressed Sampling for High Frequency Receivers Applications.” 2011. Thesis, University of Gävle. Accessed January 22, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

bi, xiaofei. “Compressed Sampling for High Frequency Receivers Applications.” 2011. Web. 22 Jan 2021.

Vancouver:

bi x. Compressed Sampling for High Frequency Receivers Applications. [Internet] [Thesis]. University of Gävle; 2011. [cited 2021 Jan 22]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

bi x. Compressed Sampling for High Frequency Receivers Applications. [Thesis]. University of Gävle; 2011. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-10877

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Duke University

6. Werner-Allen, Jonathan. Structural and Kinetic Characterization of RNA Polymerase II C-Terminal Domain Phosphatase Ssu72 and Development of New Methods for NMR Studies of Large Proteins .

Degree: 2011, Duke University

  Ssu72 is a protein phosphatase that selectively targets phosphorylated serine residues at the 5th position (pS5) in the heptad repeats of the C-terminal domain… (more)

Subjects/Keywords: Biochemistry; cis proline; NMR; RNAPII CTD; SCRUB; sparse sampling; Ssu72

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APA (6th Edition):

Werner-Allen, J. (2011). Structural and Kinetic Characterization of RNA Polymerase II C-Terminal Domain Phosphatase Ssu72 and Development of New Methods for NMR Studies of Large Proteins . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/5022

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Werner-Allen, Jonathan. “Structural and Kinetic Characterization of RNA Polymerase II C-Terminal Domain Phosphatase Ssu72 and Development of New Methods for NMR Studies of Large Proteins .” 2011. Thesis, Duke University. Accessed January 22, 2021. http://hdl.handle.net/10161/5022.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Werner-Allen, Jonathan. “Structural and Kinetic Characterization of RNA Polymerase II C-Terminal Domain Phosphatase Ssu72 and Development of New Methods for NMR Studies of Large Proteins .” 2011. Web. 22 Jan 2021.

Vancouver:

Werner-Allen J. Structural and Kinetic Characterization of RNA Polymerase II C-Terminal Domain Phosphatase Ssu72 and Development of New Methods for NMR Studies of Large Proteins . [Internet] [Thesis]. Duke University; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10161/5022.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Werner-Allen J. Structural and Kinetic Characterization of RNA Polymerase II C-Terminal Domain Phosphatase Ssu72 and Development of New Methods for NMR Studies of Large Proteins . [Thesis]. Duke University; 2011. Available from: http://hdl.handle.net/10161/5022

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

7. Kim, Youngchun. Signal acquisition challenges in mobile systems.

Degree: PhD, Electrical and Computer Engineering, 2018, University of Texas – Austin

 In recent decades, the advent of mobile computing has changed human lives by providing information that was not available in the past. The mobile computing… (more)

Subjects/Keywords: Sparse signal processing; Compressed sensing; Random sampling; Data converter; Sequential detection

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APA (6th Edition):

Kim, Y. (2018). Signal acquisition challenges in mobile systems. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68089

Chicago Manual of Style (16th Edition):

Kim, Youngchun. “Signal acquisition challenges in mobile systems.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 22, 2021. http://hdl.handle.net/2152/68089.

MLA Handbook (7th Edition):

Kim, Youngchun. “Signal acquisition challenges in mobile systems.” 2018. Web. 22 Jan 2021.

Vancouver:

Kim Y. Signal acquisition challenges in mobile systems. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2152/68089.

Council of Science Editors:

Kim Y. Signal acquisition challenges in mobile systems. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68089


University of Florida

8. Xu, Xie. Volumetric Data Reconstruction from Irregular Samples and Compressively Sensed Measurements.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2014, University of Florida

Sampling and reconstruction of volumetric data are ubiquitous throughout biomedical imaging, scientific simulation, and visualization applications. In this dissertation, we focus on the reconstruction of… (more)

Subjects/Keywords: Approximation; Boxes; Conceptual lattices; Datasets; Face centered cubic lattices; Interpolation; Mathematical lattices; Sampling rates; Signals; Supernova remnants; box-splines  – compressed-sensing  – reconstruction  – sampling  – sparse-approximation  – sparse-representation  – volumetric-data

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Xu, X. (2014). Volumetric Data Reconstruction from Irregular Samples and Compressively Sensed Measurements. (Doctoral Dissertation). University of Florida. Retrieved from https://ufdc.ufl.edu/UFE0046527

Chicago Manual of Style (16th Edition):

Xu, Xie. “Volumetric Data Reconstruction from Irregular Samples and Compressively Sensed Measurements.” 2014. Doctoral Dissertation, University of Florida. Accessed January 22, 2021. https://ufdc.ufl.edu/UFE0046527.

MLA Handbook (7th Edition):

Xu, Xie. “Volumetric Data Reconstruction from Irregular Samples and Compressively Sensed Measurements.” 2014. Web. 22 Jan 2021.

Vancouver:

Xu X. Volumetric Data Reconstruction from Irregular Samples and Compressively Sensed Measurements. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2021 Jan 22]. Available from: https://ufdc.ufl.edu/UFE0046527.

Council of Science Editors:

Xu X. Volumetric Data Reconstruction from Irregular Samples and Compressively Sensed Measurements. [Doctoral Dissertation]. University of Florida; 2014. Available from: https://ufdc.ufl.edu/UFE0046527


McMaster University

9. Pournaghi, Reza. Coded Acquisition of High Speed Videos with Multiple Cameras.

Degree: PhD, 2015, McMaster University

High frame rate video (HFV) is an important investigational tool in sciences, engineering and military. In ultrahigh speed imaging, the obtainable temporal, spatial and spectral… (more)

Subjects/Keywords: Compressive Sensing; High Speed Video; Coded Acquisition; Random Sampling; Sparse Representation; Digital Cameras; Rolling Shutter

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pournaghi, R. (2015). Coded Acquisition of High Speed Videos with Multiple Cameras. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/16887

Chicago Manual of Style (16th Edition):

Pournaghi, Reza. “Coded Acquisition of High Speed Videos with Multiple Cameras.” 2015. Doctoral Dissertation, McMaster University. Accessed January 22, 2021. http://hdl.handle.net/11375/16887.

MLA Handbook (7th Edition):

Pournaghi, Reza. “Coded Acquisition of High Speed Videos with Multiple Cameras.” 2015. Web. 22 Jan 2021.

Vancouver:

Pournaghi R. Coded Acquisition of High Speed Videos with Multiple Cameras. [Internet] [Doctoral dissertation]. McMaster University; 2015. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11375/16887.

Council of Science Editors:

Pournaghi R. Coded Acquisition of High Speed Videos with Multiple Cameras. [Doctoral Dissertation]. McMaster University; 2015. Available from: http://hdl.handle.net/11375/16887


Delft University of Technology

10. Ortiz Jimenez, Guillermo (author). Multidomain Graph Signal Processing: Learning and Sampling.

Degree: 2018, Delft University of Technology

 In this era of data deluge, we are overwhelmed with massive volumes of extremely complex datasets. Data generated today is complex because it lacks a… (more)

Subjects/Keywords: deep learning; graph signal processing; sparse sampling; product graphs; submodular optimization; tensors

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APA (6th Edition):

Ortiz Jimenez, G. (. (2018). Multidomain Graph Signal Processing: Learning and Sampling. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:6fd6b441-1694-473e-a317-b60d168f19a7

Chicago Manual of Style (16th Edition):

Ortiz Jimenez, Guillermo (author). “Multidomain Graph Signal Processing: Learning and Sampling.” 2018. Masters Thesis, Delft University of Technology. Accessed January 22, 2021. http://resolver.tudelft.nl/uuid:6fd6b441-1694-473e-a317-b60d168f19a7.

MLA Handbook (7th Edition):

Ortiz Jimenez, Guillermo (author). “Multidomain Graph Signal Processing: Learning and Sampling.” 2018. Web. 22 Jan 2021.

Vancouver:

Ortiz Jimenez G(. Multidomain Graph Signal Processing: Learning and Sampling. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 Jan 22]. Available from: http://resolver.tudelft.nl/uuid:6fd6b441-1694-473e-a317-b60d168f19a7.

Council of Science Editors:

Ortiz Jimenez G(. Multidomain Graph Signal Processing: Learning and Sampling. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:6fd6b441-1694-473e-a317-b60d168f19a7


University of Illinois – Urbana-Champaign

11. Lam, Fan. A subspace approach to high-resolution magnetic resonance spectroscopic imaging.

Degree: PhD, Electrical & Computer Engr, 2015, University of Illinois – Urbana-Champaign

 With its unique capability to obtain spatially resolved biochemical profiles from the human body noninvasively, magnetic resonance spectroscopic imaging (MRSI) has been recognized as a… (more)

Subjects/Keywords: Magnetic resonance spectroscopic imaging; Partial separability; Subspace modeling; Low-rank model; Sparse sampling

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APA (6th Edition):

Lam, F. (2015). A subspace approach to high-resolution magnetic resonance spectroscopic imaging. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/78611

Chicago Manual of Style (16th Edition):

Lam, Fan. “A subspace approach to high-resolution magnetic resonance spectroscopic imaging.” 2015. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed January 22, 2021. http://hdl.handle.net/2142/78611.

MLA Handbook (7th Edition):

Lam, Fan. “A subspace approach to high-resolution magnetic resonance spectroscopic imaging.” 2015. Web. 22 Jan 2021.

Vancouver:

Lam F. A subspace approach to high-resolution magnetic resonance spectroscopic imaging. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2015. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2142/78611.

Council of Science Editors:

Lam F. A subspace approach to high-resolution magnetic resonance spectroscopic imaging. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/78611

12. Ajamian, Tzila. Exploration de l’Acquisition Comprimée appliquée à la Réflectométrie : Exploration of Compressive Sampling for Wire Diagnosis Systems Based on Reflectometry.

Degree: Docteur es, Signal, Image, Vision, 2019, Ecole centrale de Nantes

La réflectométrie, une technique utilisée en diagnostic filaire, permet la détection et la localisation de défauts des câbles. Alors que, les Convertisseurs Analogique-Numérique sont indispensables… (more)

Subjects/Keywords: Diagnostic filaire; Acquisition comprimée; Matrices parcimonieuses; Wire diagnosis; Compressive Sampling; Sparse matrices

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ajamian, T. (2019). Exploration de l’Acquisition Comprimée appliquée à la Réflectométrie : Exploration of Compressive Sampling for Wire Diagnosis Systems Based on Reflectometry. (Doctoral Dissertation). Ecole centrale de Nantes. Retrieved from http://www.theses.fr/2019ECDN0040

Chicago Manual of Style (16th Edition):

Ajamian, Tzila. “Exploration de l’Acquisition Comprimée appliquée à la Réflectométrie : Exploration of Compressive Sampling for Wire Diagnosis Systems Based on Reflectometry.” 2019. Doctoral Dissertation, Ecole centrale de Nantes. Accessed January 22, 2021. http://www.theses.fr/2019ECDN0040.

MLA Handbook (7th Edition):

Ajamian, Tzila. “Exploration de l’Acquisition Comprimée appliquée à la Réflectométrie : Exploration of Compressive Sampling for Wire Diagnosis Systems Based on Reflectometry.” 2019. Web. 22 Jan 2021.

Vancouver:

Ajamian T. Exploration de l’Acquisition Comprimée appliquée à la Réflectométrie : Exploration of Compressive Sampling for Wire Diagnosis Systems Based on Reflectometry. [Internet] [Doctoral dissertation]. Ecole centrale de Nantes; 2019. [cited 2021 Jan 22]. Available from: http://www.theses.fr/2019ECDN0040.

Council of Science Editors:

Ajamian T. Exploration de l’Acquisition Comprimée appliquée à la Réflectométrie : Exploration of Compressive Sampling for Wire Diagnosis Systems Based on Reflectometry. [Doctoral Dissertation]. Ecole centrale de Nantes; 2019. Available from: http://www.theses.fr/2019ECDN0040


University of Maryland

13. Reddy, Nagilla Dikpal. SPARSE ACQUISITION AND RECONSTRUCTION FOR SOME COMPUTER VISION PROBLEMS.

Degree: Electrical Engineering, 2011, University of Maryland

Sparse representation, acquisition and reconstruction of signals guided by theory of Compressive Sensing (CS) has become an active research research topic over the last few… (more)

Subjects/Keywords: Electrical engineering; Background Subtraction; Compressive Sensing; High Speed Cameras; Sampling; Sparse Representation; Video Reconstrcution

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APA (6th Edition):

Reddy, N. D. (2011). SPARSE ACQUISITION AND RECONSTRUCTION FOR SOME COMPUTER VISION PROBLEMS. (Thesis). University of Maryland. Retrieved from http://hdl.handle.net/1903/11984

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Reddy, Nagilla Dikpal. “SPARSE ACQUISITION AND RECONSTRUCTION FOR SOME COMPUTER VISION PROBLEMS.” 2011. Thesis, University of Maryland. Accessed January 22, 2021. http://hdl.handle.net/1903/11984.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Reddy, Nagilla Dikpal. “SPARSE ACQUISITION AND RECONSTRUCTION FOR SOME COMPUTER VISION PROBLEMS.” 2011. Web. 22 Jan 2021.

Vancouver:

Reddy ND. SPARSE ACQUISITION AND RECONSTRUCTION FOR SOME COMPUTER VISION PROBLEMS. [Internet] [Thesis]. University of Maryland; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/1903/11984.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Reddy ND. SPARSE ACQUISITION AND RECONSTRUCTION FOR SOME COMPUTER VISION PROBLEMS. [Thesis]. University of Maryland; 2011. Available from: http://hdl.handle.net/1903/11984

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Oklahoma State University

14. Mamun, S. M. Abdullah Al. Data-driven sparse estimation of nonlinear fluid flows.

Degree: Mechanical and Aerospace Engineering, 2020, Oklahoma State University

 Estimation of full state fluid flow from limited observations is central for many practical applications in physics and engineering science. Fluid flows are manifestations of… (more)

Subjects/Keywords: deep neural network; latin hypercube sampling; linear estimation; nonlinear estimation; pod; sparse estimation

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APA (6th Edition):

Mamun, S. M. A. A. (2020). Data-driven sparse estimation of nonlinear fluid flows. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/325505

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mamun, S M Abdullah Al. “Data-driven sparse estimation of nonlinear fluid flows.” 2020. Thesis, Oklahoma State University. Accessed January 22, 2021. http://hdl.handle.net/11244/325505.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mamun, S M Abdullah Al. “Data-driven sparse estimation of nonlinear fluid flows.” 2020. Web. 22 Jan 2021.

Vancouver:

Mamun SMAA. Data-driven sparse estimation of nonlinear fluid flows. [Internet] [Thesis]. Oklahoma State University; 2020. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11244/325505.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mamun SMAA. Data-driven sparse estimation of nonlinear fluid flows. [Thesis]. Oklahoma State University; 2020. Available from: http://hdl.handle.net/11244/325505

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Colorado

15. Peng, Ji. Uncertainty Quantification via Sparse Polynomial Chaos Expansion.

Degree: PhD, Mechanical Engineering, 2015, University of Colorado

  Uncertainty quantification (UQ) is an emerging research area that aims to develop methods for accurate predictions of quantities of interest (QoI's) from complex engineering… (more)

Subjects/Keywords: Basis design; Compressive sampling; Polynomial chaos expansion; Sparse approximation; Uncertainty quantification; Applied Mathematics; Mechanical Engineering; Statistics and Probability

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APA (6th Edition):

Peng, J. (2015). Uncertainty Quantification via Sparse Polynomial Chaos Expansion. (Doctoral Dissertation). University of Colorado. Retrieved from https://scholar.colorado.edu/mcen_gradetds/112

Chicago Manual of Style (16th Edition):

Peng, Ji. “Uncertainty Quantification via Sparse Polynomial Chaos Expansion.” 2015. Doctoral Dissertation, University of Colorado. Accessed January 22, 2021. https://scholar.colorado.edu/mcen_gradetds/112.

MLA Handbook (7th Edition):

Peng, Ji. “Uncertainty Quantification via Sparse Polynomial Chaos Expansion.” 2015. Web. 22 Jan 2021.

Vancouver:

Peng J. Uncertainty Quantification via Sparse Polynomial Chaos Expansion. [Internet] [Doctoral dissertation]. University of Colorado; 2015. [cited 2021 Jan 22]. Available from: https://scholar.colorado.edu/mcen_gradetds/112.

Council of Science Editors:

Peng J. Uncertainty Quantification via Sparse Polynomial Chaos Expansion. [Doctoral Dissertation]. University of Colorado; 2015. Available from: https://scholar.colorado.edu/mcen_gradetds/112

16. Khaled, Yassine. Contribution à la commande et l'observation des systèmes dynamiques continus sous mesures clairsemées : Contribution to the observation and control of continuous systems under sparse measurements.

Degree: Docteur es, Génie électrique et électronique - Cergy, 2014, Cergy-Pontoise; Université Abou Bekr Belkaid (Tlemcen, Algérie)

Les travaux de cette thèse portent sur l'analyse de stabilité des systèmes dynamiques impulsionnels et la synthèse d'observateurs pour les systèmes dynamiques continus avec mesures… (more)

Subjects/Keywords: Observateurs impulsionnels; Mesures clairsemées; Systèmes sous échantillonnage; Acquisition compressive; Systèmes dynamiques impulsionnels; Chaos; Impulsive observer; Sparse measurement; System under sampling; System under sampling; Impulsive dynamical systems; Chaos

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APA (6th Edition):

Khaled, Y. (2014). Contribution à la commande et l'observation des systèmes dynamiques continus sous mesures clairsemées : Contribution to the observation and control of continuous systems under sparse measurements. (Doctoral Dissertation). Cergy-Pontoise; Université Abou Bekr Belkaid (Tlemcen, Algérie). Retrieved from http://www.theses.fr/2014CERG0706

Chicago Manual of Style (16th Edition):

Khaled, Yassine. “Contribution à la commande et l'observation des systèmes dynamiques continus sous mesures clairsemées : Contribution to the observation and control of continuous systems under sparse measurements.” 2014. Doctoral Dissertation, Cergy-Pontoise; Université Abou Bekr Belkaid (Tlemcen, Algérie). Accessed January 22, 2021. http://www.theses.fr/2014CERG0706.

MLA Handbook (7th Edition):

Khaled, Yassine. “Contribution à la commande et l'observation des systèmes dynamiques continus sous mesures clairsemées : Contribution to the observation and control of continuous systems under sparse measurements.” 2014. Web. 22 Jan 2021.

Vancouver:

Khaled Y. Contribution à la commande et l'observation des systèmes dynamiques continus sous mesures clairsemées : Contribution to the observation and control of continuous systems under sparse measurements. [Internet] [Doctoral dissertation]. Cergy-Pontoise; Université Abou Bekr Belkaid (Tlemcen, Algérie); 2014. [cited 2021 Jan 22]. Available from: http://www.theses.fr/2014CERG0706.

Council of Science Editors:

Khaled Y. Contribution à la commande et l'observation des systèmes dynamiques continus sous mesures clairsemées : Contribution to the observation and control of continuous systems under sparse measurements. [Doctoral Dissertation]. Cergy-Pontoise; Université Abou Bekr Belkaid (Tlemcen, Algérie); 2014. Available from: http://www.theses.fr/2014CERG0706

17. Wajer, F.T.A.W. Non-Cartesian MRI scan time reduction through sparse sampling.

Degree: 2001, Ponsen & Looijen

 Non-Cartesian MRI Scan-Time Reduction through Sparse Sampling Magnetic resonance imaging (MRI) signals are measured in the Fourier domain, also called k-space. Samples of the MRI… (more)

Subjects/Keywords: magnetic resonance; k-space; gridding; bayesian reconstruction; sparse sampling; irregular sampling

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APA (6th Edition):

Wajer, F. T. A. W. (2001). Non-Cartesian MRI scan time reduction through sparse sampling. (Doctoral Dissertation). Ponsen & Looijen. Retrieved from http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec

Chicago Manual of Style (16th Edition):

Wajer, F T A W. “Non-Cartesian MRI scan time reduction through sparse sampling.” 2001. Doctoral Dissertation, Ponsen & Looijen. Accessed January 22, 2021. http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec.

MLA Handbook (7th Edition):

Wajer, F T A W. “Non-Cartesian MRI scan time reduction through sparse sampling.” 2001. Web. 22 Jan 2021.

Vancouver:

Wajer FTAW. Non-Cartesian MRI scan time reduction through sparse sampling. [Internet] [Doctoral dissertation]. Ponsen & Looijen; 2001. [cited 2021 Jan 22]. Available from: http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec.

Council of Science Editors:

Wajer FTAW. Non-Cartesian MRI scan time reduction through sparse sampling. [Doctoral Dissertation]. Ponsen & Looijen; 2001. Available from: http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; urn:NBN:nl:ui:24-uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec ; http://resolver.tudelft.nl/uuid:60b5f3ca-4700-4822-8f58-92c6987cd5ec


Delft University of Technology

18. Chepuri, S.P. Sparse Sensing for Statistical Inference: Theory, Algorithms, and Applications.

Degree: 2016, Delft University of Technology

 In today's society, we are flooded with massive volumes of data in the order of a billion gigabytes on a daily basis from pervasive sensors.… (more)

Subjects/Keywords: sparse sensing; sensor networks; sampling; estimation; detection; filtering; localization; clock synchronization

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APA (6th Edition):

Chepuri, S. P. (2016). Sparse Sensing for Statistical Inference: Theory, Algorithms, and Applications. (Doctoral Dissertation). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9

Chicago Manual of Style (16th Edition):

Chepuri, S P. “Sparse Sensing for Statistical Inference: Theory, Algorithms, and Applications.” 2016. Doctoral Dissertation, Delft University of Technology. Accessed January 22, 2021. http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9.

MLA Handbook (7th Edition):

Chepuri, S P. “Sparse Sensing for Statistical Inference: Theory, Algorithms, and Applications.” 2016. Web. 22 Jan 2021.

Vancouver:

Chepuri SP. Sparse Sensing for Statistical Inference: Theory, Algorithms, and Applications. [Internet] [Doctoral dissertation]. Delft University of Technology; 2016. [cited 2021 Jan 22]. Available from: http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9.

Council of Science Editors:

Chepuri SP. Sparse Sensing for Statistical Inference: Theory, Algorithms, and Applications. [Doctoral Dissertation]. Delft University of Technology; 2016. Available from: http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; urn:NBN:nl:ui:24-uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9 ; http://resolver.tudelft.nl/uuid:7776e6e3-5ea8-4aaa-892f-c26011bf96b9

19. Schwartz, Tal Shimon. Data-guided statistical sparse measurements modeling for compressive sensing.

Degree: 2013, University of Waterloo

 Digital image acquisition can be a time consuming process for situations where high spatial resolution is required. As such, optimizing the acquisition mechanism is of… (more)

Subjects/Keywords: compressive sensing; compressed sampling; digital image acquisition; sparse measurements

Sparse Measurements Model and Framework 17 3.1 Model for Constructing a Sampling Pattern… …x7B;φk }M k=1 ϕk : k th column in sampling basis Φ ϕT,k : k th sparse column in… …for a greatly reduced sampling rate through the use of sparse measurements (samples… …to the CS sparse measurement model (2.22, 2.23) using sampling basis {φk… …near the origin and sparse sampling in the periphery. The coherence between the sparsity and… 

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APA (6th Edition):

Schwartz, T. S. (2013). Data-guided statistical sparse measurements modeling for compressive sensing. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/7418

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Schwartz, Tal Shimon. “Data-guided statistical sparse measurements modeling for compressive sensing.” 2013. Thesis, University of Waterloo. Accessed January 22, 2021. http://hdl.handle.net/10012/7418.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Schwartz, Tal Shimon. “Data-guided statistical sparse measurements modeling for compressive sensing.” 2013. Web. 22 Jan 2021.

Vancouver:

Schwartz TS. Data-guided statistical sparse measurements modeling for compressive sensing. [Internet] [Thesis]. University of Waterloo; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/10012/7418.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Schwartz TS. Data-guided statistical sparse measurements modeling for compressive sensing. [Thesis]. University of Waterloo; 2013. Available from: http://hdl.handle.net/10012/7418

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Cambridge

20. Higson, Edward John. Bayesian methods and machine learning in astrophysics.

Degree: PhD, 2019, University of Cambridge

 This thesis is concerned with methods for Bayesian inference and their applications in astrophysics. We principally discuss two related themes: advances in nested sampling (Chapters… (more)

Subjects/Keywords: Machine Learning; Bayesian Inference; Nested sampling; Cosmology; Black Holes; Gravitational Waves; Neural Networks; Regression; Astrophysics; Sparsity; Parameter Estimation; Bayesian Evidence; Bayesian; Statistics; Bayesian Sparse Reconstruction; Computational Methods; Error Analysis; Dynamic Nested Sampling; nestcheck; perfectns; dyPolyChord; dynesty; Image Processing; Sparse Reconstruction; Planck; diagnostic tests; PolyChord; MultiNest; Hubble Space Telescope; Fitting; Nonparametric statistics

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APA (6th Edition):

Higson, E. J. (2019). Bayesian methods and machine learning in astrophysics. (Doctoral Dissertation). University of Cambridge. Retrieved from https://doi.org/10.17863/CAM.36974 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929

Chicago Manual of Style (16th Edition):

Higson, Edward John. “Bayesian methods and machine learning in astrophysics.” 2019. Doctoral Dissertation, University of Cambridge. Accessed January 22, 2021. https://doi.org/10.17863/CAM.36974 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929.

MLA Handbook (7th Edition):

Higson, Edward John. “Bayesian methods and machine learning in astrophysics.” 2019. Web. 22 Jan 2021.

Vancouver:

Higson EJ. Bayesian methods and machine learning in astrophysics. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2021 Jan 22]. Available from: https://doi.org/10.17863/CAM.36974 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929.

Council of Science Editors:

Higson EJ. Bayesian methods and machine learning in astrophysics. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://doi.org/10.17863/CAM.36974 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929


Indian Institute of Science

21. Satyanarayana, J V. Efficient Design of Embedded Data Acquisition Systems Based on Smart Sampling.

Degree: PhD, Faculty of Engineering, 2018, Indian Institute of Science

 Data acquisition from multiple analog channels is an important function in many embedded devices used in avionics, medical electronics, robotics and space applications. It is… (more)

Subjects/Keywords: Analog-To-Digital Converters; Smart-Sampling Data Acquisition; Embedded Data Acquisition Systems; Sparse Signals; Embedded Systems; Compressed Sensing; Signal Processing; Multiplexed Compressed Sensing; Multiplexed Signal Acquisition; Data Acquisition; MOSAICS; Multiple Sparse Signals; Compact Embedded Designs; Correlated Signals; Multiplexed Optimal Signal Acquisition Involving Compressed Sensing; Electrical Engineering

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APA (6th Edition):

Satyanarayana, J. V. (2018). Efficient Design of Embedded Data Acquisition Systems Based on Smart Sampling. (Doctoral Dissertation). Indian Institute of Science. Retrieved from http://etd.iisc.ac.in/handle/2005/3518

Chicago Manual of Style (16th Edition):

Satyanarayana, J V. “Efficient Design of Embedded Data Acquisition Systems Based on Smart Sampling.” 2018. Doctoral Dissertation, Indian Institute of Science. Accessed January 22, 2021. http://etd.iisc.ac.in/handle/2005/3518.

MLA Handbook (7th Edition):

Satyanarayana, J V. “Efficient Design of Embedded Data Acquisition Systems Based on Smart Sampling.” 2018. Web. 22 Jan 2021.

Vancouver:

Satyanarayana JV. Efficient Design of Embedded Data Acquisition Systems Based on Smart Sampling. [Internet] [Doctoral dissertation]. Indian Institute of Science; 2018. [cited 2021 Jan 22]. Available from: http://etd.iisc.ac.in/handle/2005/3518.

Council of Science Editors:

Satyanarayana JV. Efficient Design of Embedded Data Acquisition Systems Based on Smart Sampling. [Doctoral Dissertation]. Indian Institute of Science; 2018. Available from: http://etd.iisc.ac.in/handle/2005/3518


Georgia Tech

22. Mena Arias, Dario Alberto. Characterization of matrix valued BMO by commutators and sparse domination of operators.

Degree: PhD, Mathematics, 2018, Georgia Tech

 In the first part of this thesis, we characterize the space of matrix-valued, two-parameters BMO functions by using commutators with the Hilbert transform. The second… (more)

Subjects/Keywords: BMO; Commutators; Sparse operators; Sparse; Sparse forms

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APA (6th Edition):

Mena Arias, D. A. (2018). Characterization of matrix valued BMO by commutators and sparse domination of operators. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59857

Chicago Manual of Style (16th Edition):

Mena Arias, Dario Alberto. “Characterization of matrix valued BMO by commutators and sparse domination of operators.” 2018. Doctoral Dissertation, Georgia Tech. Accessed January 22, 2021. http://hdl.handle.net/1853/59857.

MLA Handbook (7th Edition):

Mena Arias, Dario Alberto. “Characterization of matrix valued BMO by commutators and sparse domination of operators.” 2018. Web. 22 Jan 2021.

Vancouver:

Mena Arias DA. Characterization of matrix valued BMO by commutators and sparse domination of operators. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/1853/59857.

Council of Science Editors:

Mena Arias DA. Characterization of matrix valued BMO by commutators and sparse domination of operators. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59857


Delft University of Technology

23. Desmedt, S.G.L. (author). Dimension-adaptive sparse grid for industrial applications using Sobol variances.

Degree: 2015, Delft University of Technology

The area of interest for this study is the field of uncertainty quantification in computational fluid dynamics. The goal is to contribute to a new… (more)

Subjects/Keywords: Sparse grid

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APA (6th Edition):

Desmedt, S. G. L. (. (2015). Dimension-adaptive sparse grid for industrial applications using Sobol variances. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:09f5dfed-5185-401c-9bbd-065130fe2bda

Chicago Manual of Style (16th Edition):

Desmedt, S G L (author). “Dimension-adaptive sparse grid for industrial applications using Sobol variances.” 2015. Masters Thesis, Delft University of Technology. Accessed January 22, 2021. http://resolver.tudelft.nl/uuid:09f5dfed-5185-401c-9bbd-065130fe2bda.

MLA Handbook (7th Edition):

Desmedt, S G L (author). “Dimension-adaptive sparse grid for industrial applications using Sobol variances.” 2015. Web. 22 Jan 2021.

Vancouver:

Desmedt SGL(. Dimension-adaptive sparse grid for industrial applications using Sobol variances. [Internet] [Masters thesis]. Delft University of Technology; 2015. [cited 2021 Jan 22]. Available from: http://resolver.tudelft.nl/uuid:09f5dfed-5185-401c-9bbd-065130fe2bda.

Council of Science Editors:

Desmedt SGL(. Dimension-adaptive sparse grid for industrial applications using Sobol variances. [Masters Thesis]. Delft University of Technology; 2015. Available from: http://resolver.tudelft.nl/uuid:09f5dfed-5185-401c-9bbd-065130fe2bda


University of Illinois – Urbana-Champaign

24. Ravishankar, Saiprasad. Adaptive sparse representations and their applications.

Degree: PhD, Electrical & Computer Engr, 2014, University of Illinois – Urbana-Champaign

 The sparsity of signals and images in a certain transform domain or dictionary has been exploited in many applications in signal processing, image processing, and… (more)

Subjects/Keywords: Inverse problems; Computer vision; Classification; Structured overcomplete transform learning; Union of transforms; Overcomplete transform learning; Structured transforms; Convex formulation; Real-time applications; Big data; Online learning; Adaptive Sampling; Image reconstruction; Block Coordinate descent; Blind compressed sensing; Convergence guarantees; Efficient updates; Closed-form solutions; Machine learning; Nonconvex optimization; Alternating minimization; Doubly sparse transform learning; Square transform learning; Adaptive sparse models; Denoising; dictionary learning; Magnetic resonance imaging; Compressed sensing; Sparse representations; Sparsifying transform learning

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APA (6th Edition):

Ravishankar, S. (2014). Adaptive sparse representations and their applications. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/88322

Chicago Manual of Style (16th Edition):

Ravishankar, Saiprasad. “Adaptive sparse representations and their applications.” 2014. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed January 22, 2021. http://hdl.handle.net/2142/88322.

MLA Handbook (7th Edition):

Ravishankar, Saiprasad. “Adaptive sparse representations and their applications.” 2014. Web. 22 Jan 2021.

Vancouver:

Ravishankar S. Adaptive sparse representations and their applications. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2014. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2142/88322.

Council of Science Editors:

Ravishankar S. Adaptive sparse representations and their applications. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/88322

25. Li, Yi. Sublinear Time Algorithms for the Sparse Recovery Problem.

Degree: PhD, Computer Science & Engineering, 2013, University of Michigan

 In the sparse recovery problem, we have a signal x in R^N that is sparse; i.e., it consists of k significant entries (heavy hitters) while… (more)

Subjects/Keywords: Sublinear-time Algorithms; Sparse Recovery Problem; Off-the-Grid Fourier Sampling; Computer Science; Engineering

…LIST OF ALGORITHMS Algorithm 1.1 General framework of the sparse recovery problem… …ABSTRACT Sublinear Time Algorithms for the Sparse Recovery Problem by Yi Li Chair: Martin… …Strauss In the sparse recovery problem, we have a signal x ∈ RN that is sparse; i.e., it… …expressed in the same mathematical formulation, called the sparse recovery problem. This problem… …compressive sensing group at Rice University. In the sparse recovery problem, we have a signal x of… 

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APA (6th Edition):

Li, Y. (2013). Sublinear Time Algorithms for the Sparse Recovery Problem. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/102438

Chicago Manual of Style (16th Edition):

Li, Yi. “Sublinear Time Algorithms for the Sparse Recovery Problem.” 2013. Doctoral Dissertation, University of Michigan. Accessed January 22, 2021. http://hdl.handle.net/2027.42/102438.

MLA Handbook (7th Edition):

Li, Yi. “Sublinear Time Algorithms for the Sparse Recovery Problem.” 2013. Web. 22 Jan 2021.

Vancouver:

Li Y. Sublinear Time Algorithms for the Sparse Recovery Problem. [Internet] [Doctoral dissertation]. University of Michigan; 2013. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2027.42/102438.

Council of Science Editors:

Li Y. Sublinear Time Algorithms for the Sparse Recovery Problem. [Doctoral Dissertation]. University of Michigan; 2013. Available from: http://hdl.handle.net/2027.42/102438

26. Merlet, Sylvain. Acquisition compressée en IRM de diffusion : Compressive sensing in diffusion MRI.

Degree: Docteur es, Automatique, traitement du signal et des images, 2013, Nice

Cette thèse est consacrée à l'élaboration de nouvelles méthodes d'acquisition et de traitement de données en IRM de diffusion (IRMd) afin de caractériser la diffusion… (more)

Subjects/Keywords: IRM de diffusion; Acquisition compressée; Reconstruction parcimonieuse; Apprentissage de dictionnaire; Propagateur de diffusion; Diffusion MRI; Compressive sensing; Sparse coding; Dictionary learning; Q-space sampling; Q-ball imaging; Ensemble average propagator; Diffusion spectrum imaging

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APA (6th Edition):

Merlet, S. (2013). Acquisition compressée en IRM de diffusion : Compressive sensing in diffusion MRI. (Doctoral Dissertation). Nice. Retrieved from http://www.theses.fr/2013NICE4061

Chicago Manual of Style (16th Edition):

Merlet, Sylvain. “Acquisition compressée en IRM de diffusion : Compressive sensing in diffusion MRI.” 2013. Doctoral Dissertation, Nice. Accessed January 22, 2021. http://www.theses.fr/2013NICE4061.

MLA Handbook (7th Edition):

Merlet, Sylvain. “Acquisition compressée en IRM de diffusion : Compressive sensing in diffusion MRI.” 2013. Web. 22 Jan 2021.

Vancouver:

Merlet S. Acquisition compressée en IRM de diffusion : Compressive sensing in diffusion MRI. [Internet] [Doctoral dissertation]. Nice; 2013. [cited 2021 Jan 22]. Available from: http://www.theses.fr/2013NICE4061.

Council of Science Editors:

Merlet S. Acquisition compressée en IRM de diffusion : Compressive sensing in diffusion MRI. [Doctoral Dissertation]. Nice; 2013. Available from: http://www.theses.fr/2013NICE4061


Brno University of Technology

27. Berky, Martin. Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence.

Degree: 2019, Brno University of Technology

 This diploma thesis deals with separation of moving objects from static unchanging background in video sequence. Thesis contains description of common method of separation and… (more)

Subjects/Keywords: Řídká reprezentace signálů; komprimované snímání; medianova metoda; Matlab; video sekvence; separace pozadí; pohyblivé objekty; zpracování obrazu; Sparse signal reprezentation; compressive sampling; median method; Matlab; video sequence; background substraction; moving objects; image processing

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APA (6th Edition):

Berky, M. (2019). Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/180568

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Berky, Martin. “Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence.” 2019. Thesis, Brno University of Technology. Accessed January 22, 2021. http://hdl.handle.net/11012/180568.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Berky, Martin. “Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence.” 2019. Web. 22 Jan 2021.

Vancouver:

Berky M. Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11012/180568.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Berky M. Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/180568

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Missouri University of Science and Technology

28. Zhang, Ling. Sparse emission source microscopy for rapid emission source imaging.

Degree: M.S. in Electrical Engineering, Electrical Engineering, Missouri University of Science and Technology

  "In Paper I, Sparse Emission Source Microscopy (ESM) methodology will be introduced and discussed for the localization of major EMI radiation sources in complex… (more)

Subjects/Keywords: EMI Coupling Paths; EMI Mitigation; Emission Source Microscopy; Optical Transceiver Modules; Source Localization; Sparse Sampling; Electrical and Computer Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, L. (n.d.). Sparse emission source microscopy for rapid emission source imaging. (Masters Thesis). Missouri University of Science and Technology. Retrieved from https://scholarsmine.mst.edu/masters_theses/7729

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Chicago Manual of Style (16th Edition):

Zhang, Ling. “Sparse emission source microscopy for rapid emission source imaging.” Masters Thesis, Missouri University of Science and Technology. Accessed January 22, 2021. https://scholarsmine.mst.edu/masters_theses/7729.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

MLA Handbook (7th Edition):

Zhang, Ling. “Sparse emission source microscopy for rapid emission source imaging.” Web. 22 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Zhang L. Sparse emission source microscopy for rapid emission source imaging. [Internet] [Masters thesis]. Missouri University of Science and Technology; [cited 2021 Jan 22]. Available from: https://scholarsmine.mst.edu/masters_theses/7729.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Council of Science Editors:

Zhang L. Sparse emission source microscopy for rapid emission source imaging. [Masters Thesis]. Missouri University of Science and Technology; Available from: https://scholarsmine.mst.edu/masters_theses/7729

Note: this citation may be lacking information needed for this citation format:
No year of publication.

29. Haldar, Justin P. Constrained imaging: denoising and sparse sampling.

Degree: PhD, 1200, 2011, University of Illinois – Urbana-Champaign

 Magnetic resonance imaging (MRI) is a powerful tool for studying the anatomy, physiology, and metabolism of biological systems. Despite the fact that MRI was introduced… (more)

Subjects/Keywords: Magnetic Resonance Imaging; Constrained Reconstruction; Denoising; Sparse Sampling; Regularization; Compressed Sensing; Sparsity; Low Rank

…5.2.1 Rank-Constrained Matrix Recovery with the PS Model . 5.2.2 Sampling Considerations and… …5.5.1 Specialized Sampling Versus Random Sampling . . . . 5.5.2 Selection of L… …acquisition in conventional MRI is typically modeled as sampling in the spatial Fourier domain (… …x7D;M m=1 is the set of k-space sampling locations, {dm }M m=1 is the set of… …Image resolution. MR image resolution is a function of the Fourier-domain sampling pattern… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Haldar, J. P. (2011). Constrained imaging: denoising and sparse sampling. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/24286

Chicago Manual of Style (16th Edition):

Haldar, Justin P. “Constrained imaging: denoising and sparse sampling.” 2011. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed January 22, 2021. http://hdl.handle.net/2142/24286.

MLA Handbook (7th Edition):

Haldar, Justin P. “Constrained imaging: denoising and sparse sampling.” 2011. Web. 22 Jan 2021.

Vancouver:

Haldar JP. Constrained imaging: denoising and sparse sampling. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2011. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/2142/24286.

Council of Science Editors:

Haldar JP. Constrained imaging: denoising and sparse sampling. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2011. Available from: http://hdl.handle.net/2142/24286


Brno University of Technology

30. Berky, Martin. Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence.

Degree: 2019, Brno University of Technology

 This diploma thesis deals with separation of moving objects from static unchanging background in video sequence. In this thesis are described common method of separation… (more)

Subjects/Keywords: Řídká reprezentace signálů; komprimované snímání; medianova metoda; Matlab; video sekvence; separace pozadí; pohyblivé objekty; zpracování obrazu; Sparse signal reprezentation; compressive sampling; median method; Matlab; video sequence; background substraction; moving objects; image processing

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Berky, M. (2019). Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/177522

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Berky, Martin. “Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence.” 2019. Thesis, Brno University of Technology. Accessed January 22, 2021. http://hdl.handle.net/11012/177522.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Berky, Martin. “Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence.” 2019. Web. 22 Jan 2021.

Vancouver:

Berky M. Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence. [Internet] [Thesis]. Brno University of Technology; 2019. [cited 2021 Jan 22]. Available from: http://hdl.handle.net/11012/177522.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Berky M. Vytvoření bezchybné fotografie z narušené videosekvence: Clean photo out of corrupted videosequence. [Thesis]. Brno University of Technology; 2019. Available from: http://hdl.handle.net/11012/177522

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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