A Study of High-Speed Hamming Distance Detection Circuit Utilizing a Neuron CMOS Inverter

Abstract

This study tackles the challenge of optimizing associative memory for efficient data retrieval from large databases, crucial in real-time processing. The authors specifically address the issue of increased detection time in the minimum Hamming distance search associative memory, particularly as the number of data bits grows. This memory system utilizes Hamming distance as a key metric to identify the most similar reference data. Our contribution is the development of a new Hamming distance detection circuit employing neuron Complementary Metal Oxide Semiconductor (CMOS) inverters. This proposed circuit significantly outperforms existing models in terms of operational speed. The effectiveness and improved performance of the circuit are validated through simulations using HSPICE, a type of Simulation Program with Integrated Circuit Emphasis (SPICE) demonstrating its potential for more efficient real-time data retrieval applications.