A new signal reconstruction method in compressed sensing. (July 2018)

• Record Type: Journal Article
• Authors: Chen, Xuan
• Is Part Of: Computers & electrical engineering. Volume 69(2018)
• Page Start: 865
• Page End: 880
• Publication Date: 2018-07
• Subjects: Signal -- Reconstruction -- Compressed sensing -- l1 norm; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2017.12.027
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Aiming at the shortcomings of being rough by using the l 1 norm to replace the original signal for signal reconstruction, this paper first constructs the l 1 norm's smooth approximation function and studies the monotonicity and convergence of the optimal solution sequence. Second, the pseudo-function || x || p (0 < p < 1) replaces || x ||1 in signal reconstruction, and the maximum entropy function is used to smooth lp (0 < p < 1). In this paper, the algorithm's performance is analyzed and its feasibility is verified using one- and two-dimensional signal reconstruction. This algorithm has smaller error than other compression reconstruction algorithms, better structure, and a more convenient calculation.