Comparison of four learning algorithms for multilayer perceptron with FIR synapses

In recent years many training algorithms for dynamic neural networks have been proposed. As a matter of fact, it is well known that the exact training algorithm for dynamic networks, is non causal and can be implemented only in batch mode. In this paper we present a comparison of three online training algorithms for dynamic networks, where each synapsis is modelled by an FIR filter. In order to evaluate performance and computational complexity of the various algorithms, several computer simulations of dynamical system identifications have been carried out.