You are now following this Submission
- You will see updates in your followed content feed
- You may receive emails, depending on your communication preferences
The demo of the algorithm EA-SRC is given in 'Demo_Classification_EASRC';
In addition to the main algorithm, the main contributions which utilizes the regularized ELM with a computational efficiency LOO method (RELM-LOO) is also given, with demos in 'Demo_Classification' and 'Demo_Regression';
The regressor includes the regularized ELM with a computational efficiency LOO method (RELM-LOO) is given in the folder '/utilities' named as 'regressor';
The folder '/l1ls' includes four representative sparse reconstruction algorithms;
Two classification applications and one regression application are included for illustration.
Cite As
Kai Zhang (2026). Code for the Extreme learning machine and adaptive sparse representation algorithm (EA-SRC) (https://se.mathworks.com/matlabcentral/fileexchange/58005-code-for-the-extreme-learning-machine-and-adaptive-sparse-representation-algorithm-ea-src), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0.0 (6.67 MB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 | . |
