2011Unpublished venueRequires access

High signal-to-noise ratio gain by stochastic resonance in an unconventional bistable system

Pin Wan, Yiju Zhan, Hui Zheng

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Abstract

We report that the signal-to-noise ratio (SNR) can be improved by the stochastic resonance (SR) in an unconventional bistable system. The system is driven by Gaussian white noise and a sinusoidal signal, and studied by using the second-order Runge-Kutta method. We find that the SNR and the SNR gain exhibit the stochastic resonance behavior, and the SNR gain greatly exceeds unity on some occasions. This result is the latest development of the unconventional bistable stochastic resonance, and has potential applications in the signal detection, processing and communications.

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What this paper is about

We report that the signal-to-noise ratio (SNR) can be improved by the stochastic resonance (SR) in an unconventional bistable system. The system is driven by Gaussian white noise and a sinusoidal signal, and studied by using the second-order Runge-Kutta method. We find that the SNR and the SNR gain exhibit the stochastic resonance behavior, and the SNR gain greatly exceeds unity on some occasions. This result is the latest development of the unconventional bistable stochastic resonance, and has potential applications in the signal detection, processing and communications.

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Available abstract

We report that the signal-to-noise ratio (SNR) can be improved by the stochastic resonance (SR) in an unconventional bistable system. The system is driven by Gaussian white noise and a sinusoidal signal, and studied by using the second-order Runge-Kutta method. We find that the SNR and the SNR gain exhibit the stochastic resonance behavior, and the SNR gain greatly exceeds unity on some occasions. This result is the latest development of the unconventional bistable stochastic resonance, and has potential applications in the signal detection, processing and communications.

Key concepts: Stochastic resonance, Bistability, White noise, Signal-to-noise ratio (imaging), SIGNAL (programming language), Signal transfer function, Noise (video), Gaussian noise

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