Ridge polynomial networks in pattern recognition

Ridge polynomial networks (RPNs) are a special class of high order neural networks, which are computationally much more efficient than traditional high order neural networks. Motivated by the ability of high order NNs to perform shift and rotation invariant pattern recognition tasks, we apply RPNs for function approximation and character recognition. We are using features from the image block representation of the characters and traditional invariant moments. The results are quite favoring and show that RPNs can be used effectively in pattern recognition problems.