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Dictionary Learning, DL, tries to express a series of data as a sparse combination of the elements stored in a dictionary. The dictionary is noted by \({\textbf{D}} = [\textbf{d}_1, \ldots \textbf{d}_M] \in {\mathbb R}^{d\times M}\) , the data \(\textbf{x}_i \in \mathbb R^{d}\) , \(i=1, \ldots , K\) are grouped in the columns of matrix \(\textbf{X}\) , and the data representation in the dictionary by vectors \(\textbf{r}_j \in \mathbb R^M\) , \(j=1, \ldots , K\) .

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Dictionary Learning

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Francisco Chinesta,
  • Elías Cueto,
  • Victor Champaney,
  • Chady Ghnatios,
  • Amine Ammar,
  • Nicolas Hascoët,
  • David González,
  • Icíar Alfaro,
  • Daniele Di Lorenzo,
  • Angelo Pasquale,
  • Dominique Baillargeat

摘要

Dictionary Learning, DL, tries to express a series of data as a sparse combination of the elements stored in a dictionary. The dictionary is noted by \({\textbf{D}} = [\textbf{d}_1, \ldots \textbf{d}_M] \in {\mathbb R}^{d\times M}\) , the data \(\textbf{x}_i \in \mathbb R^{d}\) , \(i=1, \ldots , K\) are grouped in the columns of matrix \(\textbf{X}\) , and the data representation in the dictionary by vectors \(\textbf{r}_j \in \mathbb R^M\) , \(j=1, \ldots , K\) .