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Signal processing technique
Compressed sensing (also known as compressive sensing, compressive sampling, or sparse sampling) is a signal processing technique for efficiently acquiring
Compressed_sensing
Australian and American mathematician (born 1975)
arithmetic combinatorics, geometric combinatorics, probability theory, compressed sensing, and analytic number theory. He is regarded by many as "the finest
Terence_Tao
Computational imaging technique
an imaging scheme is called a single-pixel camera. Combined with compressed sensing, the single-pixel camera can recover images from fewer measurements
Single-pixel_imaging
Means to measure signal processing ability
signal detection theory is called compressed sensing (or compressive sensing). The objective of compressed sensing is to recover high dimensional but
Detection_theory
Type of metric geometry
vector. This approach appears in the signal recovery framework called compressed sensing. Taxicab geometry can be used to assess the differences in discrete
Taxicab_geometry
Matrix property in linear algebra
and Terence Tao and is used to prove many theorems in the field of compressed sensing. There are no known large matrices with bounded restricted isometry
Restricted_isometry_property
In communications technology, the technique of compressed sensing (CS) may be applied to the processing of speech signals under certain conditions. In
Compressed sensing in speech signals
Compressed_sensing_in_speech_signals
In compressed sensing, the nullspace property gives necessary and sufficient conditions on the reconstruction of sparse signals using the techniques of
Nullspace_property
Sufficiency theorem for reconstructing signals from samples
signal are known (see § Sampling of non-baseband signals below and compressed sensing). In some cases (when the sample-rate criterion is not satisfied)
Nyquist–Shannon sampling theorem
Nyquist–Shannon_sampling_theorem
Signal-processing paradigm that trades precision for volume of measurements
signals, and HDR imaging with sweeping thresholds. Kaczmarz method Compressed sensing Phase retrieval Quantization (signal processing) Eamaz, Arian; Yeganegi
Sample_abundance
German applied mathematician (born 1972)
mathematician known for her research in harmonic analysis, deep learning, compressed sensing, and image processing. She has a Bavarian AI Chair for "Mathematical
Gitta_Kutyniok
French statistician (born 1970)
statistician most well known for his contributions to the field of compressed sensing and statistical hypothesis testing. He is a professor of statistics
Emmanuel_Candès
using the knowledge of the compressed signal and the measurement matrix. Mathematically, the recovery process in Compressed Sensing is finding the sparsest
Verification-based message-passing algorithms in compressed sensing
Verification-based_message-passing_algorithms_in_compressed_sensing
Electrical engineer and computer scientist
University. Her research involves studying non-convex optimization and compressed sensing algorithms used in machine learning and statistical signal processing
Yuejie_Chi
Representation learning method
sparse dictionary learning is in the field of compressed sensing or signal recovery. In compressed sensing, a high-dimensional signal can be recovered with
Sparse_dictionary_learning
Statistical procedure of testing by group
{\textbf {x}}} . Compressed sensing, which is closely related to group testing, can be used to solve this problem. In compressed sensing, the goal is to
Group_testing
Romanian mathematician
mathematician at the University of Oxford whose research interests include compressed sensing, numerical analysis, and regularisation methods in mathematical optimization
Coralia_Cartis
American mathematician
to compressed sensing and the mathematics of data". She is also a SIAM Fellow, in the 2024 class of fellows, elected "for contributions to compressed sensing
Deanna_Needell
Mathematical result
is a random orthogonal projection. The lemma has applications in compressed sensing, manifold learning, dimensionality reduction, graph embedding, and
Johnson–Lindenstrauss_lemma
Gambian mathematician
He joined the University of Edinburgh, where his PhD investigated compressed sensing and was supervised by Jared Tanner [Wikidata]. He was a member of
Bubacarr_Bah
Standard test image
and published as a test image in journals today. A 2012 paper on compressed sensing used a photo of the model Fabio Lanzoni as a test image to draw attention
Lenna
French physicist and engineer
and information theory, statistical inference, machine learning and compressed sensing. He is especially known for his work on the Stochastic block model
Florent_Krzakala
Indirectly forming images from measurements using algorithms
to improve image quality and reduce radiation dose in CT. In MRI, compressed sensing has been used to accelerate image acquisition by exploiting sparsity
Computational_imaging
Generalizations of Nyquist-Shannon sampling theorem for reconstructing signals
theory was developed (see the section Beyond Nyquist below) using compressed sensing. In particular, the theory, using signal processing language, is described
Nonuniform_sampling
Any technique to improve resolution of an imaging system beyond conventional limits
tomography), subspace decomposition-based methods (e.g. MUSIC) and compressed sensing-based algorithms (e.g., SAMV) are employed to achieve SR over standard
Super-resolution_imaging
Topics referred to by the same term
elliptic functions Carbon steel Cirrostratus cloud Citizen science Compressed sensing, a signal processing technique for reconstructing a signal using underdetermined
CS
Spatial anti-aliasing method
density Poisson-disc sample generation with directional variation for compressed sensing in MRI". Magnetic Resonance Imaging. 77: 186–193. doi:10.1016/j.mri
Supersampling
Mathematical optimization problem
statistics (see the LASSO method of regularization), image compression and compressed sensing. When δ = 0 {\displaystyle \delta =0} , this problem becomes basis
Basis_pursuit_denoising
Norwegian mathematician
Local: Getting More from Compressed Sensing", SIAM News (October 2017). Books Adcock, Ben; Hansen, Anders C. (2021). Compressive imaging: structure, sampling
Anders_C._Hansen
Optimization problem
to Compressive Sensing. Springer, 2013, ISBN 9780817649487, pp. 77–110 Shaobing Chen, David Donoho: Basis Pursuit Terence Tao: Compressed Sensing. Mahler
Basis_pursuit
Reconstruction of quantum states based on measurements
a sparse representation. The method of compressed quantum process tomography (CQPT) uses the compressed sensing technique and applies the sparsity assumption
Quantum_tomography
Class of algorithms for solving constrained optimization problems
Lagrangian methods in fields such as total variation denoising and compressed sensing. In particular, a variant of the standard augmented Lagrangian method
Augmented_Lagrangian_method
coding theorist from the former Yugoslavia, known for her work in compressed sensing, low-density parity-check codes, and DNA digital data storage. She
Olgica_Milenkovic
American electrical engineer
control, developed various algorithms and performance analyses for compressed sensing and structured signal recovery, studied epidemic spread in complex
Babak_Hassibi
Combining information from two detectors
pseudothermal source case. Recently, it was shown that the principles of 'Compressed-Sensing' can be directly utilized to reduce the number of measurements required
Ghost_imaging
Mathematical concept
especially in error correcting codes and signal processing (for example compressed sensing), consists in an upper bound on the number of variables which may
Underdetermined_system
Egyptian-American professor and engineer
performance. His edited book Compressive Sensing for Urban Radar (CRC Press, 2014) was among the first to bridge compressive sensing theory with practical urban
Moeness_Amin
American statistician
(multiscale geometric analysis), development of wavelets for denoising and compressed sensing. He was elected a Member of the American Philosophical Society in
David_Donoho
complementarity of wavelets and noiselets means that noiselets can be used in compressed sensing to reconstruct a signal (such as an image) which has a compact representation
Noiselet
Israeli academic and engineer
Her research interests include sampling methods and A/D design, compressed sensing, detection and estimation theory, optimization for signal processing
Yonina_Eldar
Algorithm that estimates unknowns from a series of measurements over time
noisy observations. Recent works utilize notions from the theory of compressed sensing/sampling, such as the restricted isometry property and related probabilistic
Kalman_filter
Romanian-American computer scientist
guidance for aortic valve implantation, enhanced stent visualization, compressed sensing for Magnetic Resonance, and automatic patient positioning for Computed
Dorin_Comaniciu
Image processing task
multiple sensors. More recently, a new class of approaches leverage compressed sensing, to regularize an optimization problem, and recover stripe free images
Image_destriping
Mathematical limit applied in statistical physics
and image restoration, large-system CDMA multiuser detection, and compressed sensing. In the statistical physics of systems with quenched disorder, any
Replica_trick
Bulgarian applied mathematician
known for her research in image processing, inverse problems, and compressed sensing. After working as a science journalist and engineer in Bulgaria, Nikolova
Mila_Nikolova
French mathematical statistician
learning researcher known for her work in stochastic optimization, compressed sensing, and multi-armed bandit problems. She works in Germany as a professor
Alexandra_Carpentier
British applied mathematician
optimisation, imaging sciences, and machine learning", including research on compressed sensing and on instability in image reconstruction techniques that use deep
Clarice_Poon
Chinese-American electrical engineer
University. Her research interests include statistical signal processing, compressed sensing, cognitive radio, and localization in wireless sensor networks. Tian
Zhi_Tian
Concept in mathematics
connection between sparse representation modeling and deep-learning. Compressed sensing Sparse dictionary learning K-SVD Lasso (statistics) Regularization
Sparse_approximation
American physicist and academic
and reconstruction, including parallel imaging and detector arrays, compressed sensing, and artificial intelligence (AI). Sodickson has been a leader in
Daniel_K._Sodickson
Method for solving certain optimization problems
used for ℓ1 minimization and smoothed ℓp minimization, p < 1, in compressed sensing problems. It has been proved that the algorithm has a linear rate
Iteratively reweighted least squares
Iteratively_reweighted_least_squares
Approximation method in statistics
reason, the Lasso and its variants are fundamental to the field of compressed sensing. An extension of this approach is elastic net regularization. Least-squares
Least_squares
Compressed sensing spectroscopic technique
molecular factor computing, is an approach to the development of compressed sensing spectroscopic instruments, particularly for industrial applications
Multivariate optical computing
Multivariate_optical_computing
Fewest dependent columns in a matrix
Isometry Property, the Nullspace Property, and Related Concepts in Compressed Sensing". IEEE Transactions on Information Theory. 60 (2): 1248–1259. arXiv:1205
Spark_(mathematics)
Medical imaging technique
extremely high field strengths inhibit their popularity. However, recent compressed sensing-based software algorithms (e.g., SAMV) have been proposed to achieve
Magnetic_resonance_imaging
Type of visual artifact
PMID 30040634. Lee D, Yoo J, Ye JC (April 2017). "Deep residual learning for compressed sensing MRI". 2017 IEEE 14th International Symposium on Biomedical Imaging
MRI_artifact
Noise removal process during image processing
known as the primal dual method. Due in part to much research in compressed sensing in the mid-2000s, there are many algorithms, such as the split-Bregman
Total_variation_denoising
German physicist (born 1970)
technologies and to the study of complex quantum systems. Work on compressed sensing quantum state tomography he has contributed to has been influential
Jens_Eisert
Approach to finding numerical solutions of ordinary differential equations
methods. There are other modifications which uses techniques from compressive sensing to minimize memory usage In the film Hidden Figures, Katherine Johnson
Euler_method
Spanish physicist and materials scientist
Hossein; Khaled, Nadia; Atienza, David; Vandergheynst, Pierre (2011). "Compressed Sensing for Real-Time Energy-Efficient ECG Compression on Wireless Body Sensor
David_Atienza
Portuguese engineer, academic
(2007). "Gradient projection for sparse reconstruction: Application to compressed sensing and other inverse problems". IEEE Journal of Selected Topics in Signal
Mario_A._T._Figueiredo
Mathematics concept
parameter designs for investigating noise factor impacts on responses Compressed sensing for signal processing and under-determined linear systems (inverse
Hadamard_matrix
Indian-American neuroscientist
olfactory bulb, influencing sensory processing and perceptual stability. Compressed sensing and modeling: In collaboration with theorists, Murthy co-developed
Venkatesh_N._Murthy
British statistician (born 1965)
Digital audio restoration: a statistical model based approach and Compressed sensing & sparse filtering. Godsill is currently a director of CEDAR Audio
Simon_Godsill
Award in applied mathematics
outstanding contribution to "applied mathematics in the highest and broadest sense". The recipient of the prize has to be a member of one of the awarding societies
Cathleen_Synge_Morawetz_Prize
Satellite Sensor, Sun sensor Catadioptric sensor Chemoreceptor Compressive sensing Cryogenic particle detectors Dew warning Diffusion tensor imaging
List_of_sensors
Indian-American physicist and clinical researcher
trajectories. Using accelerated acquisition and non-linear reconstruction (compressed sensing), MRSI data have been acquired within 20 minutes or so in contrast
Michael_Albert_Thomas
Biomedical engineer
imaging. She is specifically interested in image reconstruction, compressed sensing, and machine learning. Her current work involves using parallel magnetic
Leslie_Ying
Indian-American electrical engineer
an Indian-American electrical engineer known for her research in compressed sensing, robust principal component analysis, signal processing, statistical
Namrata_Vaswani
US Army UWB SAR radar
Based on Compressive Sensing Methods for UWB Radar Imaging". In Maio, Antonio; Eldar, Yonina; Haimovich, Alexander (eds.). Compressed Sensing in Radar
BoomSAR
1965 book by Bharati Krishna Tirtha
Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing (IMac4s). IEEE. pp. 465–469. doi:10.1109/iMac4s.2013.6526456. ISBN 978-1-4673-5090-7
Vedic_Mathematics
Abstraction of graph shortest cycles
is smaller otherwise. Girths of real linear matroids also arise in compressed sensing, where the same concept is referred to as the spark of a matrix. The
Matroid_girth
approaches Multiresolution analysis Singular value decomposition Compressed sensing Multiscale Geometry and Analysis in High Dimensions. September 7 –
Multiscale_geometric_analysis
Value in matrix theory
almost meeting the lower bound can be constructed by Weil's theorem. Compressed sensing Restricted isometry property Babel function Tropp, J.A. (March 2006)
Mutual coherence (linear algebra)
Mutual_coherence_(linear_algebra)
American mathematician
New Trends in Applied Harmonic Analysis: Sparse Representations, Compressed Sensing, and Multifractal Analysis. Birkhäuser. ISBN 978-3-319-27873-5. Aldroubi
Akram_Aldroubi
this method have been used also in sparse approximation problems and compressed sensing settings. Landweber, L. (1951). "An iteration formula for Fredholm
Landweber_iteration
More equations than unknowns (mathematics)
{\displaystyle x=1,} but each equation by itself has two solutions. Compressed sensing Consistency proof Integrability condition Least squares Moore–Penrose
Overdetermined_system
Framework in machine learning
algorithms, but learned. M-theory also shares some principles with compressed sensing. The theory proposes multilayered hierarchical learning architecture
M-theory_(learning_framework)
Iterative optimization algorithm
reconstruction Magnetic resonance imaging Radar Hyperspectral imaging Compressed sensing Least absolute deviations or ℓ 1 {\displaystyle \ell _{1}} -regularized
Bregman_method
Chinese statistician
analysis, and statistical decision theory, and applications to genomics, compressed sensing, chemical identification, medical imaging, and financial engineering
T._Tony_Cai
Polish computer scientist
pattern matching. He has also made contributions to the theory of compressed sensing. His work on algorithms for computing the Fourier transform of signals
Piotr_Indyk
Function spaces generalizing finite-dimensional p norm spaces
redirect targets Rudin 1987, pp. 35–36. Donoho, David L. (2006). "Compressed sensing". IEEE Transactions on Information Theory. 52 (4): 1289–1306. Bibcode:2006ITIT
Lp_space
American mathematician (born 1977)
performance guarantees for algorithms for sparse approximation and compressed sensing. In 2011, he published a paper on randomized algorithms for computing
Joel_Tropp
American optical scientist
scientist and engineer known for his work in computational imaging, compressive sensing, and gigapixel array camera systems. He is the J. W. and H. M. Goodman
David_J._Brady
Study involving matter and electromagnetic radiation
spectroscopists Metamerism (color) Multivariate optical computing – compressed sensing technique to calculate chemical information from a spectrum Operando
Spectroscopy
Image reconstruction algorithms
parameter-free superresolution tomographic reconstruction method inspired by compressed sensing, with applications in synthetic-aperture radar, computed tomography
Iterative_reconstruction
American applied mathematician
a wide variety of applied math areas including image processing, compressed sensing, and stochastic and adaptive gradient descent. Ward also worked on
Rachel_Ward_(mathematician)
French mathematician (b. 1939)
Award for Technical and Scientific Research. Wavelet Alex Grossmann Compressed sensing JPEG 2000 Ingrid Daubechies Jean Morlet Hoffman, Daniel (22 March
Yves_Meyer
and full ring-shaped transducer arrays, as well as solutions like compressed sensing, weighted factor, and iterative filtered backprojection. The result
Deep learning in photoacoustic imaging
Deep_learning_in_photoacoustic_imaging
Medical diagnostic method
reconstruction techniques (ART) or iterative solvers with regularization Compressed sensing approaches exploiting signal sparsity Deep learning-based inverters
Terahertz_tomography
Engineering professor
2016-04-01. Retrieved 2019-01-10. "Design and Analysis of High-Performance Compressed Sensing Receivers | Science and Technology". scienceandtechnology.jpl.nasa
Azita_Emami
Imaging technique
technique is called interferometric microscopy. Compressive holography applies the principles of compressed sensing to the ill-posed inverse problem of recovering
Digital_holography
Magnetic resonance imaging technique
prevalent standard, especially in clinical settings. MRF is connected to compressed sensing and shares expected benefits. Initial findings suggest that MRF could
Magnetic resonance fingerprinting
Magnetic_resonance_fingerprinting
Multidimensional data algorithm
changing the core algorithm. Matching pursuit is related to the field of compressed sensing and has been extended by researchers in that community. Notable extensions
Matching_pursuit
English mathematician
although they do not appear explicitly in this work. In the context of compressed sensing, frames (partial bases of Hilbert spaces) derived from this construction
Raymond_Paley
Repeating pattern of swirling vortices
Bayındır, Cihan; Namlı, Barış (2021). "Efficient sensing of von Kármán vortices using compressive sensing". Computers & Fluids. 226 104975. arXiv:2005.08325
Kármán_vortex_street
German chemist and medical physicist (born 1951)
PMID 18299913 ".: ESMRMB - Online :.: Inverse imaging, sparse sampling, compressed sensing, and more". www.esmrmb.org. Archived from the original on 2015-10-04
Jürgen_Hennig
Filling in missing entries of a matrix
n {\displaystyle nr\log n} . The concept of incoherence arose in compressed sensing. It is introduced in the context of matrix completion to ensure the
Matrix_completion
Spectrograph equipped with an integral field unit
imaging techniques, based for example on tomographic reconstruction or compressed sensing using a coded aperture, have been developed. One major advantage of
Integral_field_spectrograph
Branch of machine learning
Applications of artificial intelligence Comparison of deep learning software Compressed sensing Differentiable programming Echo state network List of artificial intelligence
Deep_learning
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