A Sparsity Preestimated Adaptive Matching Pursuit Algorithm
Open Access
- 30 April 2021
- journal article
- research article
- Published by Hindawi Limited in Journal of Electrical and Computer Engineering
- Vol. 2021, 1-8
- https://doi.org/10.1155/2021/5598180
Abstract
In the matching pursuit algorithm of compressed sensing, the traditional reconstruction algorithm needs to know the signal sparsity. The sparsity adaptive matching pursuit (SAMP) algorithm can adaptively approach the signal sparsity when the sparsity is unknown. However, the SAMP algorithm starts from zero and iterates several times with a fixed step size to approximate the true sparsity, which increases the runtime. To increase the run speed, a sparsity preestimated adaptive matching pursuit (SPAMP) algorithm is proposed in this paper. Firstly, the sparsity preestimated strategy is used to estimate the sparsity, and then the signal is reconstructed by the SAMP algorithm with the preestimated sparsity as the iterative initial value. The method reconstructs the signal from the preestimated sparsity, which reduces the number of iterations and greatly speeds up the run efficiency.Keywords
Funding Information
- Doctoral Scientific Research Foundation of Liaoning Province (2020-BS-225, 2017RC10)
This publication has 19 references indexed in Scilit:
- Sparse Signal Estimation by Maximally Sparse Convex OptimizationIEEE Transactions on Signal Processing, 2014
- Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching PursuitIEEE Transactions on Information Theory, 2012
- Hard Thresholding Pursuit: An Algorithm for Compressive SensingSIAM Journal on Numerical Analysis, 2011
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samplesApplied and Computational Harmonic Analysis, 2009
- Subspace Pursuit for Compressive Sensing Signal ReconstructionIEEE Transactions on Information Theory, 2009
- Uniform Uncertainty Principle and Signal Recovery via Regularized Orthogonal Matching PursuitFoundations of Computational Mathematics, 2008
- Signal Recovery From Random Measurements Via Orthogonal Matching PursuitIEEE Transactions on Information Theory, 2007
- Compressed sensingIEEE Transactions on Information Theory, 2006
- Decoding by Linear ProgrammingIEEE Transactions on Information Theory, 2005
- Orthogonal matching pursuit: recursive function approximation with applications to wavelet decompositionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002