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.
Steven Van Vaerenbergh (2020). Kernel Adaptive Filtering Toolbox (https://www.github.com/steven2358/kafbox), GitHub. Retrieved .
New version and description update.