A library of adaptive neural networks for control purposes
Giampiero Campa, Mario Luca Fravolini, M. Napolitano · 2003
In this paper, a library of adaptive neural networks to be used within the Simulink/spl reg/ environment is presented. The library has been developed by the authors with the intent of giving to the Simulink user an easy access to a variety of adaptive approximators. The neural networks contained in the library are ready to be used and interchanged within the user's application. Different from existing neural network collections and toolboxes, in this library, a neural network is strictly treated as a dynamic system with its inputs, outputs and states, and the "dynamics" of the approximation process are therefore considered as an essential part of this "system". The library is introduced and the featured network architectures are analyzed in detail. Finally, as an example, a comparison is performed between two of the presented networks.