Kernel Adaptive Filtering Toolbox

Version 2.0.0.0 (720 KB) by Steven Van Vaerenbergh
A Matlab benchmarking toolbox for kernel adaptive filtering
5.0
(2)
2.7K Downloads
Updated 5 May 2023
View License on GitHub

Kernel adaptive filters are online machine learning algorithms based on kernel methods. Typical applications include time-series prediction, nonlinear adaptive filtering, tracking and online learning for nonlinear regression. This toolbox includes algorithms, demos, and tools to compare their performance.

Cite As

Steven Van Vaerenbergh (2025). Kernel Adaptive Filtering Toolbox (https://github.com/steven2358/kafbox), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2009b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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data

demo

demo/literature/liu2010kernel

demo/literature/richard2009online

demo/literature/vanvaerenbergh2006sliding

demo/literature/vanvaerenbergh2012kernel

demo/literature/yukawa2012multikernel

lib

lib/base

lib/profiler

lib/test

lib/util

lib/util/gpml

Versions that use the GitHub default branch cannot be downloaded

Version Published Release Notes
2.0.0.0

New version and description update.
1.2.0.0

edit name
1.1.0.0

update logo
1.0.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.