The utilization of grouped n-tuple logic nodes in artificial neural Single Layer Nets

Based upon the n-tuple methodology originated by Bledsoe and Browning, this paper outlines the benefits obtained by using grouped n-tuple nodes to enhance the pattern selectivity of single-layer n-tuple networks. The principles of the n-tuple and grouped node techniques are outlined and comparative results are presented. From the documented results it is confirmed that, compared with a conventional n-tuple system and with no higher memory requirements, the grouped node, Pseudo Huge Tuple (PHT) technique significantly improves the recognition confidence levels. Additionally, this technique tends to provide faster training and allows the user more flexibility in choosing system parameters.