MATLAB Source Code for L1-Norm Computation in Sparse Representation
MATLAB-based source code implementation for L1-norm calculation in sparse representation, featuring algorithm explanations and practical parameter tuning guidelines
KSVD and MOD Dictionary Learning Sparse Representation Program Code
KSVD and MOD Dictionary Learning Sparse Representation Program Code with Algorithm Implementation Details
Sparse Representation (SR) Toolbox
Application Background: This toolbox implements machine learning methodologies including sparse coding-based classification, dictionary-based dimensionality reduction with sub-dictionary learning, learning models, and linear regression/classification (LRC). It features implementations of kernel l1-regularized and/or non-negative constrained sparse coding and dictionary learning models. Key Technologies: The optimization utilizes active set, interior point, proximal, and decomposition methods. Current version: 1.9 (March 2, 2015). Freely available for academic use with commercial licenses offering advanced features and technical support.
Sparse Representation-Based Cartoon-Texture Decomposition
A sparse representation-based cartoon-texture decomposition program implementing advanced algorithms to effectively separate cartoon and texture components from images
Hottest Sparse Representation Algorithms
Code implementation from Yi Ma et al.'s PAMI paper on the most popular sparse representation algorithms
Source Code for Image Sparse Representation
This attachment contains MATLAB source code for image sparse representation, featuring fully functional implementation with configurable parameters for optimized performance across various image types.
Compressed Sensing, Sparse Representation: Entry-Level Examples and Code Implementation
Introductory examples for compressed sensing, sparse sampling, and sparse representation with practical code demonstrations
Sparse Representation Classification Program (SRC) with Algorithm Implementation
A custom-developed Sparse Representation Classification (SRC) program designed to demonstrate SRC principles and algorithms through practical code implementation and technical explanations.
Sparse Representation Orthogonal Matching Pursuit Algorithm MATLAB Source Code
MATLAB implementation of the Orthogonal Matching Pursuit algorithm for sparse signal representation with detailed code documentation and practical applications
Face Recognition System Using Sparse Representation with MATLAB GUI Implementation
A successfully implemented face recognition system based on sparse representation methodology, developed using MATLAB GUI framework with complete functionality