Sparse Impulsive Noise Corrupted Compressed Signal Recovery Using Laplace Noise Density
-
Published:2020
Issue:
Volume:
Page:261-268
-
ISSN:2190-3018
-
Container-title:Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology
-
language:
-
Short-container-title:
Author:
Wan Hongjie,Zhang Haiyun
Publisher
Springer Singapore
Reference14 articles.
1. Giacobello, D., Christensen, M.G., Murthi, M.N., et al.: Sparse linear prediction and its applications to speech processing. IEEE Trans. Audio Speech Lang. Process. 20(5), 1644–1657 (2012) 2. He, L., Carin, L.: Exploiting structure in wavelet-based Bayesian compressive sensing. IEEE Trans. Signal Process. 57(9), 3488–3497 (2009) 3. Hinojosa, C., Bacca, J., Arguello, H.: Coded aperture design for compressive spectral subspace clustering. IEEE J. Sel. Top. Signal Process. 12(6), 1589–1600 (2018) 4. An, Y., Zhang, Y., Guo, H., Wang, J.: Compressive sensing-based three-dimensional laser imaging with dual illumination. IEEE Access 7, 25708–25717 (2019) 5. Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52, 1289–1306 (2006)
|
|