Negentropy-Based Sparsity-Promoting Reconstruction with Fast Iterative Solution from Noisy Measurements

Negentropy-Based Sparsity-Promoting Reconstruction with Fast Iterative Solution from Noisy Measurements

Compressed sensing provides an elegant framework for recovering sparse signals from compressed measurements. This paper addresses the problem of sparse signal reconstruction from compressed measurements that is more robust to complex, especially non-Gaussian noise, which arises in many applications....

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Bibliographic Details
Main Authors: Yingxin Zhao, Yingjie Huang, Hong Wu, Ming Zhang, Zhiyang Liu, Shuxue Ding
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Sensors
Subjects:
compressed sensing
sparse constraint
first order Taylor expansion
fast iterative
non-Gaussian noise
Online Access:https://www.mdpi.com/1424-8220/20/18/5384

Internet

https://www.mdpi.com/1424-8220/20/18/5384

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