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A New Analysis for Support Recovery With Block Orthogonal Matching Pursuit

Haifeng Li, Jinming Wen
2019 IEEE Signal Processing Letters  
Block orthogonal matching pursuit (BOMP) is a popular greedy algorithm for recovering block sparse signals due to its high efficiency and effectiveness.  ...  By fully using the block sparsity of block sparse signals, BOMP can achieve very good recovery performance.  ...  Then our sufficient condition for the exact support recovery of block K-sparse signals with BOMP is as follows: Theorem 1.  ... 
doi:10.1109/lsp.2018.2885919 fatcat:jhx3eftafvcufcman7d6cwll74

Block-sparsity pattern recovery from noisy observations

Jun Fang, Hongbin Li
2012 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
A simple, efficient recovery method, namely, a block-version of the orthogonal matching pursuit (OMP) method, is considered in this paper and its behavior for recovering the block-sparsity pattern is analyzed  ...  Our analysis reveals that exploiting block-sparsity can improve the recovery ability and lead to a guaranteed recovery for a higher sparsity level.  ...  Recovery of block-sparse signals has been extensively studied in [3] - [5] , in which the recovery behaviors of the basis pursuit (BP), or 1 -constrained QP, and the orthogonal matching pursuit (OMP)  ... 
doi:10.1109/icassp.2012.6288626 dblp:conf/icassp/FangL12 fatcat:bxn7ctkcybam5iz2zetofmsqn4

Block Sparse Signals Recovery via Block BacktrackingBased Matching Pursuit Method

2017 Journal of Information Processing Systems  
In this paper, a new iterative algorithm for reconstructing block sparse signals, called block backtrackingbased adaptive orthogonal matching pursuit (BBAOMP) method, is proposed.  ...  Compared with existing methods, the BBAOMP method can bring some flexibility between computational complexity and reconstruction property by using the backtracking step.  ...  Acknowledgement This work is supported by Natural Science Foundation of China (No. 61601417), Natural Science Foundation of Hubei Province (No. 2016CFC717).  ... 
doi:10.3745/jips.04.0030 fatcat:yfxlbwhqnbdavc6mauyesqkqru

Stepwise Optimal Subspace Pursuit for Improving Sparse Recovery

Balakrishnan Varadarajan, Sanjeev Khudanpur, Trac D. Tran
2011 IEEE Signal Processing Letters  
We show that compared to currently popular sparsity seeking matching pursuit algorithms, each step of the proposed algorithm is locally optimal with respect to the actual objective function.  ...  We invoke a block-wise matrix inversion formula to obtain a closed-form expression for the increase (reduction) in the 2 -norm of the residue obtained by removing (adding) a single element from (to) the  ...  COMPLEXITY ANALYSIS OF GREEDY PURSUIT The following complexity analysis of GREEDY PURSUIT shows that for each iteration it requires essentially the same computation as SP, namely . A.  ... 
doi:10.1109/lsp.2010.2090143 fatcat:vwqqkrzci5biljbilbz7lfh7ie

A* orthogonal matching pursuit: Best-first search for compressed sensing signal recovery

Nazim Burak Karahanoglu, Hakan Erdogan
2012 Digital signal processing (Print)  
This manuscript proposes a novel semi-greedy recovery approach, namely A* Orthogonal Matching Pursuit (A*OMP).  ...  A*OMP performs A* search to look for the sparsest solution on a tree whose paths grow similar to the Orthogonal Matching Pursuit (OMP) algorithm.  ...  Extensive analysis of RIP conditions for ℓ 1 relaxation can be found in [22, 3, 23, 26] . Greedy Pursuits Historically, Matching Pursuit (MP) [27] is the first greedy pursuit.  ... 
doi:10.1016/j.dsp.2012.03.003 fatcat:boexqy5cn5bt7mxufhhyjhdsjm

A New Analysis for Support Performance with Block Generalized Orthogonal Matching Pursuit

C. Y. Xia, Z. L. Zhou, Chun-Bo Guo, Y. S. Hao, C. B. Hou, Agathoklis Giaralis
2021 Mathematical Problems in Engineering  
For recovering block-sparse signals with unknown block structures using compressive sensing, a block orthogonal matching pursuit- (BOMP-) like block generalized orthogonal matching pursuit (BgOMP) algorithm  ...  The proposed support conditions guarantee that BgOMP can achieve accurate recovery block-sparse signals within k iterations.  ...  ALGORITHM 1: Block generalized orthogonal matching pursuit.  ... 
doi:10.1155/2021/9438793 fatcat:htpumo22ercodogtrvldj2pene

A Robust Matching Pursuit Algorithm Using Information Theoretic Learning [article]

Miaohua Zhang, Yongsheng Gao, Changming Sun, Michael Blumenstein
2020 arXiv   pre-print
Current orthogonal matching pursuit (OMP) algorithms calculate the correlation between two vectors using the inner product operation and minimize the mean square error, which are both suboptimal when there  ...  To overcome these problems, a new OMP algorithm is developed based on the information theoretic learning (ITL), which is built on the following new techniques: (1) an ITL-based correlation (ITL-Correlation  ...  Acknowledgements This work is supported in part by Australian Research Council (ARC) under Discovery Grants DP140101075.  ... 
arXiv:2005.04541v1 fatcat:lbicglqc7fdhfhui4lpdt5227i

Uplink channel estimation for massive MIMO systems exploring joint channel sparsity

Chenhao Qi, Lenan Wu
2014 Electronics Letters  
Then a block optimised orthogonal matching pursuit (BOOMP) algorithm is proposed.  ...  The joint sparsity of uplink channels in massive multi-inputmulti-output (MIMO) systems is explored and a block sparse model is proposed for joint channel estimation.  ...  Block optimised orthogonal matching pursuit: Now we propose a BOOMP algorithm for the proposed model in (3) .  ... 
doi:10.1049/el.2014.2769 fatcat:2qld3rd7uvhohkpnjxsg2btfnu

Least Support Orthogonal Matching Pursuit Algorithm With Prior Information

Israa Sh. Tawfic, Sema Koc Kayhan
2014 Journal of Applied Computer Science Methods  
This paper proposes a new fast matching pursuit technique named Partially Known Least Support Orthogonal Matching Pursuit (PKLS-OMP) which utilizes partially known support as a prior knowledge to reconstruct  ...  We also derive sufficient condition for stable sparse signal recovery with the partially known support.  ...  Conclusions We introduce a new fast algorithm, named Partially Known Least Support Orthogonal Matching Pursuit (PKLS-OMP), for low-complexity recovery of sparse signals sampled by matrices satisfying the  ... 
doi:10.1515/jacsm-2015-0003 fatcat:v54a6ifsfrcx5bpe3ieq4twzwa

Image Inpainting Models Using Fractional Order Anisotropic Diffusion

G. Sridevi, S. Srinivas Kumar
2016 International Journal of Image Graphics and Signal Processing  
The image reconstruction algorithms with CS increase the efficiency of the overall algorithm in reconstructing the sparse signal. There are various algorithms available for recovery.  ...  These algorithms include convex minimization class, greedy pursuit algorithms. Numerous algorithms come under these classes of recovery techniques.  ...  Orthogonal matching pursuit (OMP), a greedy algorithm, basically comes into account in the form of a variant of MP (Matching Pursuit) algorithm.  ... 
doi:10.5815/ijigsp.2015.10.01 fatcat:5e7ea7po45c3zfl4b74hhkvgpa

A Survey on Compressive Sensing: Classical Results and Recent Advancements [article]

Ahmad Mousavi, Mehdi Rezaee, Ramin Ayanzadeh
2020 arXiv   pre-print
Compressive sensing is the topic that studies the associated raised questions for the possibility of a successful recovery.  ...  Thus, these results are useful and inspiring for further investigation of related questions in these emerging fields from new perspectives.  ...  Acknowledgement The authors would like to greatly thank Professors Jinglai Shen and Maziar Salahi for their meticulous comments and constructive suggestions on this work.  ... 
arXiv:1908.01014v3 fatcat:yecn4jauubfcbc5h2c7berotfi

Compressive topology identification of interconnected dynamic systems via Clustered Orthogonal Matching Pursuit

Borhan M. Sanandaji, Tyrone L. Vincent, Michael B. Wakin
2011 IEEE Conference on Decision and Control and European Control Conference  
To this end, we introduce a greedy algorithm called Clustered Orthogonal Matching Pursuit (COMP) that tackles the problem of recovering clustered-sparse signals from few measurements.  ...  We discuss the COMP algorithm and support our discussions with simulations. All authors are with the  ...  Future work includes having a more formal understanding of COMP performance, dependence of recovery performance on network coherence [8] , etc.  ... 
doi:10.1109/cdc.2011.6161181 dblp:conf/cdc/SanandajiVW11 fatcat:pis7fe7vrjh7rol6yu5tx3iemi

An Improved Toeplitz Measurement Matrix for Compressive Sensing

Xu Su, Yin Hongpeng, Chai Yi, Xiong Yushu, Tan Xue
2014 International Journal of Distributed Sensor Networks  
A hardware platform for signal efficient acquisition and reconstruction is built by field programmable gate arrays (FPGA).  ...  A proper measurement matrix for compressive sensing is significance in above processions. In most compressive sensing frameworks, random measurement matrix is employed.  ...  This Project is granted financial support from China Postdoctoral Science Foundation (2012M521676).  ... 
doi:10.1155/2014/846757 fatcat:j7czktgsp5f4darwcs44bpcbqe

LAMP: A Locally Adapting Matching Pursuit Framework for Group Sparse Signatures in Ultra-Wide Band Radar Imaging [article]

Sanghamitra Dutta, Arijit De
2014 arXiv   pre-print
Orthogonal Matching Pursuit (OMP).  ...  In this manuscript, a novel framework that we call locally adapting matching pursuit (LAMP) have been proposed for efficient reconstruction of group sparse signals from compressed measurements without  ...  Orthogonal Matching Pursuit (OMP) OMP [16] is a one of the most widely used greedy algorithm in sparse recovery.  ... 
arXiv:1411.4020v1 fatcat:pzlv57goqvhthkjmwzvid42554

Recovery of Block-Sparse Representations from Noisy Observations via Orthogonal Matching Pursuit [article]

Jun Fang, Hongbin Li
2011 arXiv   pre-print
A simple, efficient recovery method, namely, a block-version of the orthogonal matching pursuit (OMP) method, is considered in this paper and its behavior for recovering the block-sparsity pattern is analyzed  ...  Our analysis reveals that exploiting block-sparsity can improve the recovery ability and lead to a guaranteed recovery for a higher sparsity level.  ...  We are particularly interested in analyzing the recovery ability of a block-version of the orthogonal matching pursuit (OMP).  ... 
arXiv:1109.5430v1 fatcat:xxgnl4iqwjcnngetrsnjoogr2u
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