Stochastic resonance driven by Gaussian multiplicative noise
Alexander V. Barzykin, Kazuhiko Seki
Abstract
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Alexander V. Barzykin, Kazuhiko Seki
Abstract
Open-access reader
An analytically solvable linear model for stochastic resonance driven by multiplicative noise of the Gaussian type is presented. A maximum of the signal-to-noise ratio is observed both as a function of the noise intensity and as a function of the autocorrelation time. The maximum appears for low frequencies of the applied external oscillating field immediately as soon as noise correlation is introduced, and disappears as the correlation or the frequency is increased. No resonance occurs for white noise.
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An analytically solvable linear model for stochastic resonance driven by multiplicative noise of the Gaussian type is presented. A maximum of the signal-to-noise ratio is observed both as a function of the noise intensity and as a function of the autocorrelation time. The maximum appears for low frequencies of the applied external oscillating field immediately as soon as noise correlation is introduced, and disappears as the correlation or the frequency is increased. No resonance occurs for white noise.
Key concepts: Stochastic resonance, Gaussian noise, Autocorrelation, Multiplicative noise, White noise, Noise (video), Multiplicative function, Statistical physics