期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：5
DOI：10.15680/ijircce.2015.0305122
出版社：S&S Publications
摘要：Compressive Sensing acquire sparse signal significantly at very lower rate than Nyquist sampling rate.For this, a low complexity compressed sensing operation is defined and it is the combination of sampling andcompression. The signals formed from compressed sensing operation are compressible signals and a set of randomlinear measurements accurately reconstructs compressible signals with the use of nonlinear or convex reconstructionalgorithms. Basis Pursuit algorithm is one of the convex optimization algorithms to reconstruct the sparse signal. The l1minimization theory for linear programming problems is used to formulate the compressive sensing method. Interiorpoint method is used to solve the basis pursuit algorithm for sparse signal reconstruction. In this paper, themethodology of reconstructing sparse signal using basis pursuit algorithm is discussed.
