Maximum correntropy adaptation approach for robust compressive sensing reconstruction

DOI10.1016/j.ins.2018.12.039zbMath1458.94098OpenAlexW2906292261MaRDI QIDQ2004743

Yicong He, Shiyuan Wang, Fei Wang, Jiuwen Cao, Badong Chen

Publication date: 7 October 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2018.12.039

zbMATH Keywords

compressive sensingrobust methodmaximum correntropy criterioninformation-theoretic learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Sampling theory in information and communication theory (94A20)

Related Items (3)

Sparse and robust estimation with ridge minimax concave penalty ⋮ Block-sparsity regularized maximum correntropy criterion for structured-sparse system identification ⋮ Correntropy-based metric for robust twin support vector machine

Cites Work

• Maximum correntropy Kalman filter
• Iterative hard thresholding for compressed sensing
• The C-loss function for pattern classification
• The restricted isometry property and its implications for compressed sensing
• Extensions of compressed sensing
• Maximum correntropy criterion based sparse adaptive filtering algorithms for robust channel estimation under non-Gaussian environments
• Primal and dual alternating direction algorithms for \(\ell _{1}\)-\(\ell _{1}\)-norm minimization problems in compressive sensing
• Alternating Direction Algorithms for $\ell_1$-Problems in Compressive Sensing
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
• Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
• Techniques for nonlinear least squares and robust regression
• Correntropy: Properties and Applications in Non-Gaussian Signal Processing
• Compressive Sensing Signal Reconstruction by Weighted Median Regression Estimates
• Lorentzian Iterative Hard Thresholding: Robust Compressed Sensing With Prior Information
• Outlier-Robust Greedy Pursuit Algorithms in <formula formulatype="inline"><tex Notation="TeX">$\ell _{p}$</tex> </formula>-Space for Sparse Approximation
• Generalized Correntropy for Robust<?Pub _newline ?>Adaptive Filtering
• Regression Shrinkage and Selection via The Lasso: A Retrospective
• Matching pursuits with time-frequency dictionaries
• Information Theoretic Learning
• Compressed sensing
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Maximum correntropy adaptation approach for robust compressive sensing reconstruction