For help or questions, please see the Reference Manual and the Tutorial or contact the FANN Forum

FANN Features:

• Multilayer Artificial Neural Network Library in C
• Backpropagation training (RPROP, Quickprop, Batch, Incremental)
• Evolving topology training which dynamically builds and trains the ANN (Cascade2)
• Easy to use (create, train and run an ANN with just three function calls)
• Fast (up to 150 times faster execution than other libraries)
• Versatile (possible to adjust many parameters and features on-the-fly)
• Well documented (An easy to use reference manual, a 50+ page university report describing the implementation considerations etc. and an introduction article)
• Cross-platform (configure script for linux and unix, dll files for windows, project files for MSVC++ and Borland compilers are also reported to work)
• Several different activation functions implemented (including stepwise linear functions for that extra bit of speed)
• Easy to save and load entire ANNs
• Several easy to use examples (simple train example and simple test example)
• Can use both floating point and fixed point numbers (actually both float, double and int are available)
• Cache optimized (for that extra bit of speed)
• Open source (licenced under LGPL)
• Framework for easy handling of training data sets
• fannExplorer (GUI)
• FannTool (GUI)
• NeuralView (GUI)
• Simple FANN (Command line)
• C++ Bindings
• Java Bindings
• PERL Bindings
• PHP Extension
• Python Bindings
• Ruby Bindings
• Delphi Bindings
• TCL Bindings
• Lua Bindings
• Haskel Bindings
• Visual Prolog 7 Bindings
• SWI Prolog Bindings
• .NET Bindings
• Mathematica Extension
• Matlab Bindings
• Octave Extension
• Squeak Smalltalk bindings
• Pure Data Bindings
• RPM package
• Debian package