Common Spatial Patterns (CSP)

A vectorized, quick and simple implementation of the CSP algorithm.
1.1K Downloads
Updated Fri, 19 Jul 2019 16:01:24 +0000

View License

The function 'csp' performs a bearable implementation of the Common Spatial Patterns (CSP) algorithm, which consists of a binary data-driven supervised data projection of a signal by maximizing the variance of the positive class while minimizing the variance of the negative one.

Input parameters:
- X1 and X2: Signals for the positive and negative class, respectively, whose dimensions must be [classes x samples].

Output parameters:
- W: Filter matrix (mixing matrix), whose columns are spatial filters.
- lambda: Eigenvalues of each filter.
- A: Demixing matrix.

Once the W is trained, the projection of new data X must be computed as:
X_csp = W'*X;

An example of use is included in the 'csp_example.m' file.

Cite As

Víctor Martínez-Cagigal (2024). Common Spatial Patterns (CSP) (https://www.mathworks.com/matlabcentral/fileexchange/72204-common-spatial-patterns-csp), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Categories
Find more on Discrete Multiresolution Analysis in Help Center and MATLAB Answers

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.0.0