OCLeaS – A tomographic PSI Algorithm using Orthogonal Matching Pursuit and Complex Least Squares
, 2021 Matthieu Rebmeister +4 more
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Orthogonal Matching Pursuit with Tikhonov and Landweber Regularization
CoRR, 2019 The Orthogonal Matching Pursuit (OMP) for compressed sensing iterates over a scheme of support augmentation and signal estimation. We present two novel matching pursuit algorithms with intrinsic regularization of the signal estimation step that do not rely on a priori knowledge of the signal's sparsity.
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2D Orthogonal Matching Pursuit for Fully Polarimetric SAR Image Formation
Remote SensingFully polarimetric SAR provides richer scattering information than single-polarisation imaging, but multichannel sparse image formation can be computationally and memory demanding, especially when channels are processed jointly.
Daniele Bonicoli +2 more
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Ultrasound Defect Localization in Shell Structures with Lamb Waves Using Spare Sensor Array and Orthogonal Matching Pursuit Decomposition. [PDF]
Sensors (Basel), 2021 Mu W, Gao Y, Liu G.
europepmc +1 more source
Investigation on Diverse Sparse Signal Decomposition Techniques for Power Signal Representation
EnergiesPower quality disturbance signals must be continuously monitored, stored, and transmitted for effective analysis, protection, and system planning in modern power systems.
Vivek Anjali +1 more
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OMP-ELM: Orthogonal Matching Pursuit-Based Extreme Learning Machine for Regression
Journal of Intelligent Systems, 2015 Extreme learning machine (ELM) is a recent scheme for single hidden layer feed forward networks (SLFNs). It has attracted much interest in the machine intelligence and pattern recognition fields with numerous real-world applications.
Alcin Omer F. +3 more
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Joint sparse channel estimation based on angle domain and delay domain
上海师范大学学报. 自然科学版, 2017 For the channel estimation problem of multiple input multiple output(MIMO) systems in doubly-selective (DS) channels and the joint sparse characteristic in the delay domain and angle domain,a new joint sparse channel estimation scheme based on ...
Zhang Yueming +4 more
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Sparse Recovery With Orthogonal Matching Pursuit Under RIP [PDF]
IEEE Transactions on Information Theory, 2011 This paper presents a new analysis for the orthogonal matching pursuit (OMP) algorithm. It is shown that if the restricted isometry property (RIP) is satisfied at sparsity level $O(\bar{k})$, then OMP can recover a $\bar{k}$-sparse signal in 2-norm. For compressed sensing applications, this result implies that in order to uniformly recover a $\bar{k ...
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Recuperación de señales dispersas utilizando orthogonal matching pursuit (OMP)
Ingeniería e Investigación, 2009 Muestreo compresivo es una rama emergente del procesamiento de señales, basada en el hecho de que un número pequeño de proyecciones lineales no adaptativas sobre una señal compresible contiene suficiente información para reconstruirla y proce- sarla.
Adriana Patricia Lobato Polo +3 more
doaj
On efficiency of Orthogonal Matching Pursuit
, 2010 We show that if a matrix $Φ$ satisfies the RIP of order $[CK^{1.2}]$ with isometry constant $\dt = c K^{-0.2}$ and has coherence less than $1/(20 K^{0.8})$, then Orthogonal Matching Pursuit (OMP) will recover $K$-sparse signal $x$ from $y=Φx$ in at most $[CK^{1.2}]$ iterations. This result implies that $K$-sparse signal can be recovered via OMP by $M=O(
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