Fast Approximation Library

Fast Approximation Library

IES-Research team provides the fast approximation library, which is a class-set of function approximation tools, based on growing and sliding window approaches. The library is written in C++, JAVA and Matlab. It has existing bindings for C and Python. You can use it as library or pure from source. For further information read the documentation. The sources can be downloaded here.


Native C++ implementation and additional C bindings.

Native JAVA implementation.

Native Matlab implementation.

Python bindings from C++ library.

Examples (see what happens):

The video shows an example usage of ffal.
It is an segmentation of Google stock quotes from past two years. Segments are found by orthogonal polynomial sliding window function approximation, and are also represented by an orthogonal polynomial approximated by a growing window.

Waveform data set

Click here to download the waveform data set.

EuropeWindFarm data set

Please contact M.Eng. André Gensler to get access to the EuropeWindFarm data set.

GermanSolarFarm data set

Please contact M.Eng. André Gensler to get access to the GermanSolarFarm data set.

If you are searching for software we used or developed for our papers and the software is not listed above yet, feel free to send an e-mail to Prof. Dr. Bernhard Sick. Your message will be answered immediately.