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- Title
A Hybrid Orthogonal Forward-Backward Pursuit Algorithm for Partial Fourier Multiple Measurement Vectors Problem.
- Authors
Liu, Haiqiang; Hua, Gang; Zhu, Aichun; Yin, Hongsheng; Xu, Yonggang
- Abstract
In solving the partial Fourier Multiple Measurement Vectors (FMMV) problem, existing greedy pursuit algorithms such as Simultaneous Orthogonal Matching Pursuit (SOMP), Simultaneous Subspace Pursuit (SSP), Hybrid Matching Pursuit (HMP), and Forward-Backward Pursuit (FBP) suffer from low recovery ability or need sparsity as a prior information. This paper combines SOMP and FBP to propose a Hybrid Orthogonal Forward-Backward Pursuit (HOFBP) algorithm. As an iterative algorithm, each iteration of HOFBP consists of two stages. In the first stage, α indices selected by SOMP are added to the support set. In the second stage, the support set is shrank by removing β indices. The choice of α and β is critical to the performance of this algorithm. The simulation results showed that, by using proper parameters, HOFBP has better performance than other greedy pursuit algorithms at the expense of more computing time in some cases. HOFBP does not need sparsity as a prior knowledge.
- Subjects
HYBRID systems; FORWARD-backward algorithm; PROBLEM solving; ORTHOGONAL curves; SIMULATION methods &; models
- Publication
Mathematical Problems in Engineering, 2018, p1
- ISSN
1024-123X
- Publication type
Article
- DOI
10.1155/2018/5965020