2011•Acta Physica SinicaOpen access

Numerical research of signal-to-noise ratio gain on a monostable stochastic resonance

Wan Pin, Yiju Zhan, Xuecong Li, Yonghua Wang

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Abstract

We report a stochastic resonance with the signal-to-noise ratio gain in a monostable system, by the fourth-order Runge-Kutta method, and on some occasions the signal-to-noise ratio gain exceeds 1. Tuning the parameters in the monostable stochastic resonance system can change the signal-to-noise ratio gain. This research result is the latest development of the monostable stochastic resonance, and has potential applications in the signal detection, processing and communications.

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What this paper is about

We report a stochastic resonance with the signal-to-noise ratio gain in a monostable system, by the fourth-order Runge-Kutta method, and on some occasions the signal-to-noise ratio gain exceeds 1. Tuning the parameters in the monostable stochastic resonance system can change the signal-to-noise ratio gain. This research result is the latest development of the monostable stochastic resonance, and has potential applications in the signal detection, processing and communications.

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Available abstract

We report a stochastic resonance with the signal-to-noise ratio gain in a monostable system, by the fourth-order Runge-Kutta method, and on some occasions the signal-to-noise ratio gain exceeds 1. Tuning the parameters in the monostable stochastic resonance system can change the signal-to-noise ratio gain. This research result is the latest development of the monostable stochastic resonance, and has potential applications in the signal detection, processing and communications.

Key concepts: Multivibrator, Stochastic resonance, SIGNAL (programming language), Noise (video), Signal-to-noise ratio (imaging), Signal transfer function, Computer science, Physics

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