Welcome to Dictionary Learning Toolbox’s documentation!

This toolbox solves several Dictionary Learning problems, the basic one being

\[\begin{split}\begin{align} \min _{D, \mathbf{X}} & \|\mathbf{Y}-\mathbf{D} \mathbf{X}\|_{F}^{2} \\ \text { s.t. } & \left\|\mathbf{x}_{\ell}\right\|_{0} \leq s, \ell=1: N \\ & \left\|\mathbf{d}_{j}\right\|=1, j=1: n \label{eq-dl} \end{align}\end{split}\]

where \(\mathbf{Y} \in \mathbb{R}^{m \times N}\) is a given set of \(N\) signals, each of size \(m\), \(\mathbf{D} \in \mathbb{R}^{m \times n}\) is the trained dictionary, \(\mathbf{X} \in \mathbb{R}^{n \times N}\) is the sparse representation matrix (or sparse codes) and \(s\) represents the sparsity level.

Contents:

• Installation
• Support
• Dictionary Learning Algorithms
  • Algorithms
  • Methods
• Sparse Coding
• Classifiers
  • Discriminative Dictionary Learning
  • Kernel Discriminative Dictionary Learning
  • Label Consistent Dictionary Learning
  • Kernel Label Consistent Dictionary Learning
  • Dictionary Pair Learning
  • Kernel Dictionary Pair Learning
• Datasets
  • AR Face dataset
  • Caltech101 dataset
  • MNIST handwritten digits dataset
  • YaleB dataset
• References

Indices and tables

• Index

• Module Index

• Search Page