In this paper, a neural network controller for constrained robot manipulators is presented. A feedforward neural network is used to adaptively compensate for the uncertainties in ...
This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
A method for the development of empirical predictive models for complex processes is presented. The models are capable of performing accurate multi-step-ahead (MS) predictions, wh...
This paperpresents the Compaantool that automatically transforms a nestedloopprogram written in Matlab into a processnetwork specification. The processnetworkmodelof computation...
In this paper we show that rotational invariance can be improved in a neural network based EIT reconstruction approach by a suitably chosen permutation of the input data. The inpu...