# Bayesian Gates for Reliable Logical Operations under Noisy Condition

## TL;DR

This paper introduces a novel approach to designing noise-immune logical gates by integrating Bayesian inference with noisy signal computation, outperforming previous stochastic resonance methods and traditional separate transmission and computation methods.

## Contribution

It presents a new Bayesian inference-based design for noise-immune logical gates, demonstrating improved performance over existing stochastic resonance and conventional methods.

## Key findings

- Bayesian gates outperform stochastic resonance-based gates.
- The proposed approach enhances reliability in noisy conditions.
- Integrated computation and transmission improve overall system robustness.

## Abstract

The reliability of logical operations is indispensable for the reliable operation of computational systems. Since the down-sizing of micro-fabrication generates non-negligible noise in these systems, a new approach for designing noise-immune gates is required. In this paper, we demonstrate that noise-immune gates can be designed by combining Bayesian inference theory with the idea of computation over a noisy signal. To reveal their practical advantages, the performance of these gates is evaluated in comparison with a stochastic resonance-based gate proposed previously. This approach for computation is also demonstrated to be better than a conventional one that conducts information transmission and computation separately.