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Greedy orthogonal matching pursuit algorithm for sparse signal recovery in compressive sensing
J Li, Z Wu, H Feng, Q Wang… - 2014 IEEE International …, 2014 - ieeexplore.ieee.org
The sparse signal recovery problem has been the subject of extensive research in several
different communities. Tractable recovery algorithm is a crucial and fundamental theme of …
different communities. Tractable recovery algorithm is a crucial and fundamental theme of …
An efficient two-stage sparse representation method
There are a large number of methods for solving under-determined linear inverse problems.
For large-scale optimization problem, many of them have very high time complexity. We …
For large-scale optimization problem, many of them have very high time complexity. We …
Stepwise suboptimal iterative hard thresholding algorithm for compressive sensing
J Li, Y Shen, Q Wang - 2012 IEEE International Instrumentation …, 2012 - ieeexplore.ieee.org
The sparse signal reconstruction problem has been the subject of extensive research in
several different communities. Tractable reconstruction algorithm is a crucial and …
several different communities. Tractable reconstruction algorithm is a crucial and …
MIMO-OFDM 快衰落信道的稀疏自适应感知估计
周小**， 方勇， 汪敏 - 信号处理, 2010 - signal.ejournal.org.cn
在多输入多输出(MIMO)-**交频分复用(OFDM) 系统中, 怎样在较高频谱利用率的情况下对快时
变信道进行较为准确的估计是一个具有挑战性的课题. 该文在利用压缩感知理论可提高系统频谱 …
变信道进行较为准确的估计是一个具有挑战性的课题. 该文在利用压缩感知理论可提高系统频谱 …
Predicted multi-variable intelligent matching pursuit algorithm for image sequences reconstruction based on l0 minimization
D Li, Q Wang, Y Shen - Journal of Visual Communication and Image …, 2016 - Elsevier
In this paper, we study the problem of reconstructing image sequences which satisfy the
conditions that (a) the sparsity level is high in the wavelet domain and (b) the sparsity pattern …
conditions that (a) the sparsity level is high in the wavelet domain and (b) the sparsity pattern …
Edge guided compressive sensing for image reconstruction based on two-stage l0 minimization
D Li, Z Wu, Q Wang, I Member - Journal of Visual Communication and …, 2019 - Elsevier
In compressive sensing framework, the results of image reconstruction are sometimes not
accurate enough due to the downsampled measurements, especially when the sampling …
accurate enough due to the downsampled measurements, especially when the sampling …
Performance analysis of OMP algorithm in recovering magnitude decaying sparse signals in compressive sensing
The sparse signal recovery has been the subject of extensive research in several different
communities. This paper analyzes the performance of orthogonal matching pursuit (OMP) …
communities. This paper analyzes the performance of orthogonal matching pursuit (OMP) …
Performance evaluation of compressive sensing matching pursuit backtracking iterative hard thresholding algorithm for improving reconstruction
Now-a-days due to advancements in technologies most of the applications in signal
processing were using the models based on the sparse signal. Sub optimal strategies were …
processing were using the models based on the sparse signal. Sub optimal strategies were …
Sparse Representations & Compressed Sensing with application to the problem of Direction-of-Arrival estimation.
A Gretsistas - 2013 - qmro.qmul.ac.uk
The significance of sparse representations has been highlighted in numerous signal
processing applications ranging from denoising to source separation and the emerging field …
processing applications ranging from denoising to source separation and the emerging field …
Optimization and Reconstruction of EPMA Image Based on SAMP Algorithm
A **, X Li - Proceedings of the 2020 12th International Conference …, 2020 - dl.acm.org
This paper proposes an algorithm--Fourier's sparse adaptive matching pursuit algorithm
based on the Sparse Adaptive Matching Pursuit (SAMP) algorithm. SAMP is a popular …
based on the Sparse Adaptive Matching Pursuit (SAMP) algorithm. SAMP is a popular …