ABSTRACT
Threshold polynomial neural networks offer fast learning of nonlinear mappings. It achieves this by dedicating hidden layer nodes to training patterns and using a polynomial learning algorithm. This paper outlines the architecture and main features of a threshold polynomial network. The functioning of the network and results of simulation are described.
