Noise-based logic: Binary, multi-valued, or fuzzy, with optional superposition of logic states

TL;DR

This paper introduces a novel deterministic logic system using independent stochastic noise processes to represent multiple logic states, offering advantages like reduced energy use, robustness, and natural fuzzy logic representation.

Contribution

The paper presents a new noise-based logic architecture that enables binary, multi-valued, and fuzzy logic with superposition, improving robustness and efficiency over traditional systems.

Findings

Supports multi-valued logic with arbitrary N

Natural fuzzy logic representation via superposition

Enhanced robustness and reduced energy dissipation

Abstract

A new type of deterministic (non-probabilistic) computer logic system inspired by the stochasticity of brain signals is shown. The distinct values are represented by independent stochastic processes: independent voltage (or current) noises. The orthogonality of these processes provides a natural way to construct binary or multi-valued logic circuitry with arbitrary number N of logic values by using analog circuitry. Moreover, the logic values on a single wire can be made a (weighted) superposition of the N distinct logic values. Fuzzy logic is also naturally represented by a two-component superposition within the binary case (N=2). Error propagation and accumulation are suppressed. Other relevant advantages are reduced energy dissipation and leakage current problems, and robustness against circuit noise and background noises such as 1/f, Johnson, shot and crosstalk noise. Variability problems are also nonexistent because the logic value is an AC signal. A similar logic system can be built with orthogonal sinusoidal signals (different frequency or orthogonal phase) however that has an extra 1/N type slowdown compared to the noise-based logic system with increasing number of N furthermore it is less robust against time delay effects than the noise-based counterpart.