Digital hardware implementation of Self-Organising Maps

Abstract

In this paper a digital hardware implementation of the Self-Organising Maps (SOMs) for the application of handwritten digit recognition is presented. Two methods were implemented: Euclidean and Manhattan method. The highest recognition rate for both methods was calculated through three testing techniques. The highest recognition rates obtained are 71.267% and 63.667% for the Euclidean and the Manhattan methods respectively. Both methods were implemented on the Xilinx Spartan-3 200K gates (XC3S200) to compare their speed performance and area consumed.