Stochastic-Based Pattern Recognition Analysis

TL;DR

This paper introduces a stochastic logic approach for pattern recognition, utilizing Bayesian methods and pulse-based hardware to achieve significantly faster navigation system analysis compared to traditional processor-based methods.

Contribution

It presents a novel stochastic logic architecture for pattern recognition that is faster and more efficient than existing processor-based solutions.

Findings

Orders of magnitude faster than processor-based solutions

Effective in navigation system applications

Utilizes Bayesian probabilistic comparison

Abstract

In this work we review the basic principles of stochastic logic and propose its application to probabilistic-based pattern-recognition analysis. The proposed technique is intrinsically a parallel comparison of input data to various pre-stored categories using Bayesian techniques. We design smart pulse-based stochastic-logic blocks to provide an efficient pattern recognition analysis. The proposed rchitecture is applied to a specific navigation problem. The resulting system is orders of magnitude faster than processor-based solutions.