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- W2355292065 abstract "With the emergence of new compressive sensing theory,L1-norm minimization algorithm used in processing and optimizing signals has become a hot topic in recent years,because the conventional algorithms,for example,interior-point method,are inefficient in solving large-scale data.More and more fast L1-min algorithms have been proposed,all of which have their own advantages in speed and effect.This paper first introduces the L1-min algorithms and the main factors affecting the efficiency of the algorithms,and then introduces the present five major fast L1-min algorithms.Finally,based on the experimental data,it analyzes and gives an objective evaluation to the performance of these fast algorithms when dealing with large-scale data." @default.
- W2355292065 created "2016-06-24" @default.
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- W2355292065 date "2011-01-01" @default.
- W2355292065 modified "2023-09-25" @default.
- W2355292065 title "The Performance Analysis and Comparison for Fast L1-Minimization Algorithm" @default.
- W2355292065 hasPublicationYear "2011" @default.
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