Arbitrary Block-Sparse Signal Reconstruction Based on Incomplete Single Measurement Vector
Sign Up to like & getrecommendations! Published in 2017 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0528-3
Abstract: Within the compressive sensing framework, reconstruction algorithms of block-sparse signal (BSS) often have special requirements on sparsity patterns. As a result, only some particular BSSs can be reconstructed. In this paper, we present a new… read more here.
Keywords: reconstruction; block; sparse signal; sparsity ... 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
A Tutorial on Sparse Signal Reconstruction and Its Applications in Signal Processing
Sign Up to like & getrecommendations! Published in 2019 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-018-0909-2
Abstract: Sparse signals are characterized by a few nonzero coefficients in one of their transformation domains. This was the main premise in designing signal compression algorithms. Compressive sensing as a new approach employs the sparsity property… read more here.
Keywords: reconstruction; sparse signal; signal processing; sparse signals ... See more keywords
A linearly convergent algorithm for sparse signal reconstruction
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Fixed Point Theory and Applications"
DOI: 10.1007/s11784-018-0635-1
Abstract: For the sparse signal reconstruction problem in compressive sensing, we propose a projection-type algorithm without any backtracking line search based on a new formulation of the problem. Under suitable conditions, global convergence and its linear… read more here.
Keywords: sparse signal; algorithm sparse; signal reconstruction; linearly convergent ... 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
Recovery of Block-Structured Sparse Signal Using Block-Sparse Adaptive Algorithms via Dynamic Grouping
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Access"
DOI: 10.1109/access.2018.2872671
Abstract: A key point for the recovery of a block-sparse signal is how to treat the different sparsity distributed on the different parts of the considered signal. It has been shown recently that grouping the signal,… read more here.
Keywords: recovery; block; sparse signal; tex math ... See more keywords
Sparse Signal Representation, Sampling, and Recovery in Compressive Sensing Frameworks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3197594
Abstract: Compressive sensing allows the reconstruction of original signals from a much smaller number of samples as compared to the Nyquist sampling rate. The effectiveness of compressive sensing motivated the researchers for its deployment in a… read more here.
Keywords: application areas; sensing; sparse signal; sensing frameworks ... See more keywords
Continuous-Time Sparse Signal Recovery
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3447652
Abstract: This study investigates a continuous-time method for sparse signal recovery, which is suitable for analog optical circuit implementation. The proposed method is defined by a nonlinear ordinary differential equation (ODE) derived from the gradient flow… read more here.
Keywords: signal recovery; method; time; sparse signal ... See more keywords
A Novel Perspective for Source Localization in Underwater Active Electrosense Robots Based on Sparse Signal Reconstruction
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2025.3557675
Abstract: Weakly electric fish can detect and localize objects in dark and turbid environments by sensing the perturbations induced by objects in their self-generated electric field. Massive efforts have been made to develop active electrosense systems… read more here.
Keywords: electrosense robots; sparse signal; underwater active; localization ... 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
Positive Sparse Signal Denoising: What Does a CNN Learn?
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3160372
Abstract: Convolutional neural networks (CNNs) provide impressive empirical success in various tasks; however, their inner workings generally lack interpretability. In this paper, we interpret shallow CNNs that we have trained for the task of positive sparse… read more here.
Keywords: sparse signal; signal denoising; denoising cnn; positive sparse ... See more keywords