A comparison of quartic vs. binary neural network designs

Abstract

A distributed neural network referred to as a neuromic array, which is restricted to binary alphabets, has been previously introduced (Porter, 1988). The present study loosens this restriction by demonstrating the design extension to the quartic case. A natural morphism between the quartic-valued and binary-valued vector spaces is used to establish a design equivalence between the two settings. The study compares the robustness and performance of equivalent binary and quartic designs. Extensive simulations indicated that the performance of binary design eroded only slightly when transported to the quartic case. The quartic design required fewer neurons, and a higher density was achieved.<>