Surpassing the Theoretical 1-Norm Phase Transition in Compressive Sensing by Tuning the Smoothed L0 Algorithm

doi 10.1109/icassp.2013.6638820
Full Text
Abstract

Available in full text

Date
Authors
Publisher

IEEE

Related search

Tomographic SAR Inversion by $L_{1}$ -Norm Regularization—The Compressive Sensing Approach

IEEE Transactions on Geoscience and Remote Sensing
EarthPlanetary SciencesElectricalElectronic Engineering
2010English

Fast Image Decoding for Block Compressed Sensing Based Encoding by Using a Modified Smooth L0-Norm

2016English

A Fast and Accurate Two-Stage Algorithm for 1-Bit Compressive Sensing

IEICE Transactions on Information and Systems
Electronic EngineeringPattern RecognitionHardwareComputer VisionElectricalArchitectureArtificial IntelligenceSoftware
2013English

Coal Mine Video Data Detail Enhancement Algorithm Based on L0 Norm and Low Rank Analysis

European Journal of Electrical Engineering
Electronic EngineeringElectrical
2019English

Faster P-Norm Minimizing Flows, via Smoothed Q-Norm Problems

2020English

A Simple Homotopy Proximal Mapping Algorithm for Compressive Sensing

Machine Learning
Artificial IntelligenceSoftware
2018English

Digital Image Multiple Encryption Algorithm Based on Compressive Sensing

2016English

Moving Targets Tracking Based on Improved Compressive Sensing Algorithm

International Journal of Signal Processing, Image Processing and Pattern Recognition
Signal Processing
2017English

GWRA: Grey Wolf Based Reconstruction Algorithm for Compressive Sensing Signals

PeerJ Computer Science
Computer Science
2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy