Sparse representations and compressive sampling approaches in engineering mechanics: A review of theoretical concepts and diverse applications
IA Kougioumtzoglou, I Petromichelakis… - Probabilistic Engineering …, 2020 - Elsevier
A review of theoretical concepts and diverse applications of sparse representations and
compressive sampling (CS) approaches in engineering mechanics problems is provided …
compressive sampling (CS) approaches in engineering mechanics problems is provided …
Dual-color terahertz spatial light modulator for single-pixel imaging
Spatial light modulators (SLM), capable of dynamically and spatially manipulating
electromagnetic waves, have reshaped modern life in projection display and remote …
electromagnetic waves, have reshaped modern life in projection display and remote …
Review on compressive sensing algorithms for ECG signal for IoT based deep learning framework
SS Kumar, P Ramachandran - Applied Sciences, 2022 - mdpi.com
Nowadays, healthcare is becoming very modern, and the support of Internet of Things (IoT)
is inevitable in a personal healthcare system. A typical personal healthcare system acquires …
is inevitable in a personal healthcare system. A typical personal healthcare system acquires …
Full waveform LiDAR for adverse weather conditions
We present and discuss the case for full waveform pixel and image acquisition and
processing to enable LiDAR sensors to penetrate and reconstruct 3D surface maps through …
processing to enable LiDAR sensors to penetrate and reconstruct 3D surface maps through …
Sparse stable outlier-robust signal recovery under Gaussian noise
K Suzuki, M Yukawa - IEEE Transactions on Signal Processing, 2023 - ieeexplore.ieee.org
This paper presents a novel framework for sparse robust signal recovery integrating the
sparse recovery using the minimax concave (MC) penalty and robust regression called …
sparse recovery using the minimax concave (MC) penalty and robust regression called …
A refined convergence analysis of with applications to simultaneous sparse recovery and outlier detection
We consider the problem of minimizing a difference-of-convex (DC) function, which can be
written as the sum of a smooth convex function with Lipschitz gradient, a proper closed …
written as the sum of a smooth convex function with Lipschitz gradient, a proper closed …
Damage Detection in Bridge Structures through Compressed Sensing of Crowdsourced Smartphone Data
M Talebi-Kalaleh, Q Mei - Structural Control and Health …, 2024 - Wiley Online Library
Traditional bridge health monitoring methods that necessitate sensor installation are not
only costly but also time‐consuming. In contrast, utilizing smartphone data collected from …
only costly but also time‐consuming. In contrast, utilizing smartphone data collected from …
Analysis and algorithms for some compressed sensing models based on L1/L2 minimization
Recently, in a series of papers Y. Rahimi, C. Wang, H. Dong, and Y. Lou, SIAM J. Sci.
Comput., 41 (2019), pp. A3649--A3672; C. Wang, M. Tao, J. Nagy, and Y. Lou, SIAM J …
Comput., 41 (2019), pp. A3649--A3672; C. Wang, M. Tao, J. Nagy, and Y. Lou, SIAM J …
Convergence rate analysis of a sequential convex programming method with line search for a class of constrained difference-of-convex optimization problems
In this paper, we study the sequential convex programming method with monotone line
search (SCP _ls) in Z. Lu, Sequential Convex Programming Methods for a Class of …
search (SCP _ls) in Z. Lu, Sequential Convex Programming Methods for a Class of …
Robust recovery of jointly-sparse signals using minimax concave loss function
K Suzuki, M Yukawa - IEEE Transactions on Signal Processing, 2020 - ieeexplore.ieee.org
We propose a robust approach to recovering jointly sparse signals in the presence of
outliers. The robust recovery task is cast as a convex optimization problem involving a …
outliers. The robust recovery task is cast as a convex optimization problem involving a …