JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (8): 58-64.doi: 10.6040/j.issn.1671-9352.0.2016.474

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A† graded hard thresholding pursuit algorithm

SHI Zhang-lei, LI Wei-guo   

  1. College of Science, China University of Petroleum, Qingdao 266580, Shandong, China
  • Received:2016-10-13 Online:2017-08-20 Published:2017-08-03

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Abstract: Inspired by hard thresholding pursuit algorithm(HTP). A† graded hard thresholding pursuit algorithm(APGHTP)was proposed for solving compressive sensing problems. The theoretical guarantees of the new algorithm were given under restricted isometry property(RIP)condition.In the numerical experiment, regardless of whether the measured value contains error, APGHTP performance is better, which proves the sparse recovery ability of the algorithm.When recovering sparse vectors, the number of iterations required for APGHTP is the same as that of sparse vectors.

Key words: hard thresholding pursuit, Moore-Penrose inverse, compressive sensing, sparse solution

CLC Number: 

  • O242
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