Inertial algorithms with adaptive stepsizes for split variational inclusion problems and their applications to signal recovery problem
Sign Up to like & getrecommendations! Published in 2023 at "Mathematical Methods in the Applied Sciences"
DOI: 10.1002/mma.9436
Abstract: With the help of the Meir-Keeler contraction method and the Mann-type method, two adaptive inertial iterative schemes are introduced for finding solutions of the split variational inclusion problem in Hilbert spaces. The strong convergence of… read more here.
Keywords: problem; variational inclusion; split variational; signal recovery ... See more keywords
Block Sparse Signal Recovery in Compressed Sensing: Optimum Active Block Selection and Within-Block Sparsity Order Estimation
Sign Up to like & getrecommendations! Published in 2018 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0617-3
Abstract: In this paper, we develop a new algorithm for recovery of block sparse signals in compressed sensing framework based on orthogonal matching pursuit. Furthermore, we point out that a major issue in conventional sparse signal… read more here.
Keywords: recovery; order; block; sparse signal ... See more keywords
The JDTDOA algorithm applied to signal recovery: a performance analysis
Sign Up to like & getrecommendations! Published in 2017 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-017-1076-9
Abstract: This article suggests a novel method to retrieve a narrowband signal sent in a multipath environment with a delay spread considering ISI between symbols. The proposed method does not require any preamble nor known signal.… read more here.
Keywords: algorithm applied; algorithm; jdtdoa algorithm; signal recovery ... See more keywords
Sparse signal recovery for WIM measurements from undersampled data through compressed sensing
Sign Up to like & getrecommendations! Published in 2020 at "Measurement"
DOI: 10.1016/j.measurement.2019.107181
Abstract: Abstract This study presents a method to recover the signal components critical for weigh-in-motion (WIM) measurements using compressed sensing. Through a comparative study, the wavelet basis ‘bior2.4’ is selected to sparsely represent the measured signals.… read more here.
Keywords: sparse signal; wim measurements; compressed sensing; wim ... See more keywords
Insights into the HyPer biosensor as molecular tool for monitoring cellular antioxidant capacity
Sign Up to like & getrecommendations! Published in 2018 at "Redox Biology"
DOI: 10.1016/j.redox.2018.02.023
Abstract: Aerobic metabolism brings inexorably the production of reactive oxygen species (ROS), which are counterbalanced by intrinsic antioxidant defenses avoiding deleterious intracellular effects. Redox balance is the resultant of metabolic functioning under environmental inputs (i.e. diet,… read more here.
Keywords: capacity; biosensor; tool; signal recovery ... See more keywords
Robust signal recovery using the prolate spherical wave functions and maximum correntropy criterion
Sign Up to like & getrecommendations! Published in 2018 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2017.10.025
Abstract: Abstract Signal recovery is one of the most important problem in signal processing. This paper proposes a novel signal recovery method based on prolate spherical wave functions (PSWFs). PSWFs are a kind of special functions,… read more here.
Keywords: recovery; criterion; wave functions; spherical wave ... See more keywords
High-precision bearing signal recovery based on signal fusion and variable stepsize forward-backward pursuit
Sign Up to like & getrecommendations! Published in 2021 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2021.107647
Abstract: Abstract In multi-sensor, long-distance fault monitoring of rolling bearings, the bearing signals are compressively sampled, transmitted, and reconstructed according to the theory of compressive sensing. However, the reconstruction accuracy and speed are limited and are… read more here.
Keywords: based signal; high precision; fusion; pursuit ... See more keywords
A New Approach for Sparse Signal Recovery in Compressed Sensing Based on Minimizing Composite Trigonometric Function
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2855958
Abstract: Accurate signal recovery from an underdetermined system of linear equation (USLE) is a topic of considerable interest; such as compressed sensing (CS), recovery of low-rank matrix, blind source separation, and related fields. In order to… read more here.
Keywords: tex math; signal recovery; inline formula;
Clutter-Contaminated Signal Recovery in Spectral Domain for Polarimetric Weather Radar
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3063355
Abstract: The use of spectral polarimetric filters in the range-Doppler domain shows great promise for clutter mitigation in weather radar applications. One limitation of these filters is that they cannot deal with situations in which ground… read more here.
Keywords: weather radar; clutter; spectral domain; domain ... See more keywords
Successive Hypothesis Testing Based Sparse Signal Recovery and Its Application to MUD in Random Access
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2017.2648798
Abstract: Based on successive hypothesis testing, we propose an approach for sparse signal recovery and apply it to random access to detect multiple block-sparse signals over frequency-selective fading channels. By introducing the sparsity variable, the proposed… read more here.
Keywords: successive hypothesis; sparse signal; random access; hypothesis testing ... See more keywords
Phase Retrieval With Learning Unfolded Expectation Consistent Signal Recovery Algorithm
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2020.2990767
Abstract: Phase retrieval algorithms are now an important component of many modern computational imaging systems. A recently proposed scheme called generalized expectation consistent signal recovery (GEC-SR) shows better accuracy, speed, and robustness than numerous existing methods.… read more here.
Keywords: expectation consistent; phase retrieval; signal recovery; consistent signal ... See more keywords