Self-tuning of threshold for a two-state system

TL;DR

This paper investigates self-tuning of thresholds in a two-state system under periodic signals, demonstrating improved signal-to-noise ratio through analytic and simulation methods, and extending concepts to related potential systems.

Contribution

It introduces an analytic approach to self-tuning in two-state systems, showing SNR improvements across noise levels and connecting energy dissipation with stochastic resonance.

Findings

SNR improves with self-tuning in weak noise regions

Analytic tuning equations predict SNR enhancement in large noise regions

Energy transfer rate correlates with SNR behavior

Abstract

A two-state system (TSS) under time-periodic perturbations (to be regarded as input signals) is studied in connection with self-tuning (ST) of threshold and stochastic resonance (SR). By ST, we observe the improvement of signal-to-noise ratio (SNR) in a weak noise region. Analytic approach to a tuning equation reveals that SNR improvement is possible also for a large noise region and this is demonstrated by Monte Carlo simulations of hopping processes in a TSS. ST and SR are discussed from a little more physical point of energy transfer (dissipation) rate, which behaves in a similar way as SNR. Finally ST is considered briefly for a double-well potential system (DWPS), which is closely related to the TSS.