Dynamic load identification for mechanical systems: A review

R Liu, E Dobriban, Z Hou, K Qian - Archives of Computational Methods in …, 2022 - Springer
Due to the great challenges of measuring forces directly, identifying dynamic loads based on
accessible responses is a crucial problem in engineering, hel** ensure integrity and …

Application of compressive sensing in cognitive radio communications: A survey

SK Sharma, E Lagunas, S Chatzinotas… - … surveys & tutorials, 2016 - ieeexplore.ieee.org
Compressive sensing (CS) has received much attention in several fields such as digital
image processing, wireless channel estimation, radar imaging, and cognitive radio (CR) …

[PDF][PDF] Channel estimation for reconfigurable intelligent surface aided multi-user MIMO systems

J Chen, YC Liang, HV Cheng, W Yu - arxiv preprint arxiv …, 2019 - researchgate.net
Channel acquisition is one of the main challenges for the deployment of reconfigurable
intelligent surface (RIS) aided communication system. This is because RIS has a large …

Sparse methods for direction-of-arrival estimation

Z Yang, J Li, P Stoica, L **e - Academic Press Library in Signal Processing …, 2018 - Elsevier
Abstract Direction-of-arrival (DOA) estimation refers to the process of retrieving the direction
information of several electromagnetic waves/sources from the outputs of a number of …

Channel estimation for reconfigurable intelligent surface aided multi-user mmWave MIMO systems

J Chen, YC Liang, HV Cheng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Channel acquisition is one of the main challenges for the deployment of reconfigurable
intelligent surface (RIS) aided communication systems. This is because an RIS has a large …

Image super-resolution via sparse representation

J Yang, J Wright, TS Huang… - IEEE transactions on image …, 2010 - ieeexplore.ieee.org
This paper presents a new approach to single-image superresolution, based upon sparse
signal representation. Research on image statistics suggests that image patches can be well …

Sparse signal recovery with temporally correlated source vectors using sparse Bayesian learning

Z Zhang, BD Rao - IEEE Journal of Selected Topics in Signal …, 2011 - ieeexplore.ieee.org
We address the sparse signal recovery problem in the context of multiple measurement
vectors (MMV) when elements in each nonzero row of the solution matrix are temporally …

Robust joint graph sparse coding for unsupervised spectral feature selection

X Zhu, X Li, S Zhang, C Ju, X Wu - IEEE transactions on neural …, 2016 - ieeexplore.ieee.org
In this paper, we propose a new unsupervised spectral feature selection model by
embedding a graph regularizer into the framework of joint sparse regression for preserving …

Extension of SBL algorithms for the recovery of block sparse signals with intra-block correlation

Z Zhang, BD Rao - IEEE Transactions on Signal Processing, 2013 - ieeexplore.ieee.org
We examine the recovery of block sparse signals and extend the recovery framework in two
important directions; one by exploiting the signals' intra-block correlation and the other by …

Real-valued sparse Bayesian learning for DOA estimation with arbitrary linear arrays

J Dai, HC So - IEEE Transactions on Signal Processing, 2021 - ieeexplore.ieee.org
Sparse Bayesian learning (SBL) has become a popular approach for direction-of-arrival
(DOA) estimation, but its computational complexity for Bayesian inference is quite high …