Overcomplete Transform Learning With the <inline-formula> <tex-math notation="LaTeX">$log$ </tex-math></inline-formula> Regularizer

Overcomplete Transform Learning With the <inline-formula> <tex-math notation="LaTeX">$log$ </tex-math></inline-formula> Regularizer

Transform learning has been proposed as a new and effective formulation for analysis dictionary learning, where the &#x2113;<sub>0</sub> norm or the &#x2113;<sub>1</sub> norm are generally used as sparsity constraint. The sparse solutions can be obtained by the hard t...

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Bibliographic Details
Main Authors: Zhenni Li, Shengli Xie, Wuhui Chen, Zuyuan Yang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Analysis dictionary learning
transform learning
<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">log</italic> regularizer
proximal alternating minimization
Online Access:https://ieeexplore.ieee.org/document/8506348/

Internet

https://ieeexplore.ieee.org/document/8506348/

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