Incoherent dictionary learning method based on unit norm tight frame and manifold optimization for sparse representation

DOI10.1155/2016/9407503zbMath1400.94065OpenAlexW2507234158WikidataQ59141070 ScholiaQ59141070MaRDI QIDQ1793796

HongZhong Tang, Ling Zhu, Xiang Wang, Xiaogang Zhang, Xiao Li, Hua Chen

Publication date: 12 October 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/9407503

Mathematics Subject Classification ID

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

Uses Software

• Manopt

Cites Work

• On the existence of equiangular tight frames
• On the stability of the basis pursuit in the presence of noise
• Manopt, a Matlab toolbox for optimization on manifolds
• Construction of Incoherent Unit Norm Tight Frames With Application to Compressed Sensing
• Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
• Greed is Good: Algorithmic Results for Sparse Approximation
• Designing structured tight frames via an alternating projection method
• Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
• Lower bounds on the maximum cross correlation of signals (Corresp.)
• Uncertainty principles and ideal atomic decomposition
• Parametric Dictionary Design for Sparse Coding
• $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
• Designing Incoherent Frames Through Convex Techniques for Optimized Compressed Sensing
• Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization

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