A guaranteed training of binary pattern mappings using Gaussian perceptron networks

Training algorithms are introduced for single- and multiple-layered networks of Gaussian perceptrons. One characteristic of these algorithms is that they can guarantee that a network structure and the corresponding weights will be found for any arbitrarily given mapping relation of binary patterns. A number of computer simulation results are presented to demonstrate the performance of the proposed algorithms.<>