Feasibility Pump Algorithm for Sparse Representation under Laplacian Noise
The Feasibility Pump is an effective heuristic method for solving mixed integer optimization programs. In this paper the algorithm is adapted for finding the sparse representation of signals affected by Laplacian noise. Two adaptations of the algorithm, regularized and nonregularized, are proposed,...
Main Authors: | Florin Ilarion Miertoiu, Bogdan Dumitrescu |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2019-01-01
|
Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2019/5615243 |
Similar Items
-
Feasibility Pump Algorithm for Sparse Representation under Gaussian Noise
by: Florin Ilarion Miertoiu, et al.
Published: (2020-04-01) -
An Image Fusion Method Based on Sparse Representation and Sum Modified-Laplacian in NSCT Domain
by: Yuanyuan Li, et al.
Published: (2018-07-01) -
Noise Robust Speech Recognition using Sparse Representations
by: Yu-Hung Huang, et al.
Published: (2014) -
Hyperspectral image spectral-spatial classification via weighted Laplacian smoothing constraint-based sparse representation.
by: Eryang Chen, et al.
Published: (2021-01-01) -
Salt and Pepper Noise Removal with Noise Detection and a Patch-Based Sparse Representation
by: Di Guo, et al.
Published: (2014-01-01)