ANN

Adaptive Neural Networks

The adaptive Neural Network Library (Matlab 5.3.1 and later) is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.

It was developed mainly in June-July 2001 by Giampiero Campa (West Virginia University) and Mario Luca Fravolini (Perugia University). Later improvements were partially supported by the NASA Grant NCC5-685.

There are blocks that implement basically these kinds of neural networks:

Adaptive Linear Networks (ADALINE)

Multilayer Layer Perceptron Networks

Generalized Radial Basis Functions Networks

Dynamic Cell Structure (DCS) Networks with gaussian or conical basis functions

Also, a Simulink example regarding the approximation of a scalar nonlinear function is included.

Finally, the file Training.zip includes step by step instrucions on how to train the GRBF network and the supporting example.