<inline-formula> <tex-math notation="LaTeX">$\ell_P$ </tex-math></inline-formula> Norm Independently Interpretable Regularization Based Sparse Coding for Highly Correlated Data

Sparse coding, which aims at finding appropriate sparse representations of data with an overcomplete dictionary set, is a well-established signal processing methodology and has good efficiency in various areas. The varying sparse constraint can influence the performances of sparse coding algorithms...

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出版年:	IEEE Access
主要な著者:	Haoli Zhao, Shuxue Ding, Xiang Li, Lingjun Zhao
フォーマット:	論文
言語:	英語
出版事項:	IEEE 2019-01-01
主題:	Sparse coding highly correlated data <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">ℓₚ</italic> norm weighted <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">ℓ</italic>₁ norm independently interpretable weighted lasso
オンライン･アクセス:	https://ieeexplore.ieee.org/document/8691452/