Stochastic Resonance in Organic Electronic Devices

Abstract

Stochastic Resonance (SR) is a phenomenon in which noise improves the performance of a system. With the addition of noise, a weak input signal to a nonlinear system, which may exceed its threshold, is transformed into an output signal. In the other words, noise-driven signal transfer is achieved. SR has been observed in nonlinear response systems, such as biological and artificial systems, and this review will focus mainly on examples of previous studies of mathematical models and experimental realization of SR using poly(hexylthiophene)-based organic field-effect transistors (OFETs). This phenomenon may contribute to signal processing with low energy consumption. However, the generation of SR requires a noise source. Therefore, the focus is on OFETs using materials such as organic materials with unstable electrical properties and critical elements due to unidirectional signal transmission, such as neural synapses. It has been reported that SR can be observed in OFETs by application of external noise. However, SR does not occur under conditions where the input signal exceeds the OFET threshold without external noise. Here, we present an example of a study that analyzes the behavior of SR in OFET systems and explain how SR can be made observable. At the same time, the role of internal noise in OFETs will be explained.

Temperature-induced logical resonance in the Hodgkin–Huxley neuron

“…Some efforts have been devoted to implementing this new-style LSR-based logical gate. [9][10][11][12] In the past decade, LSR has received more and more attention. [13][14][15][16][17][18][19] Noise is not the only factor to induce logical resonance.…”

Control of stochastic and inverse stochastic resonances in a liquid-crystal electroconvection system using amplitude and phase noises

“…Usually, SR shows a maximal output performance peak corresponding to the signal-to-noise ratio at a moderate optimal noise level. Since Benzi et al first suggested this phenomenon and its underlying mechanism in a study on ice-age cycles [2,3], SR has been extensively investigated in various fields, including physics [4,5], chemistry [6,7], biology [8,9], information technology [10,11], and brain science [12,13]. In contrast, an opposing phenomenon known as the inverse stochastic resonance (ISR) was initially discovered in a neural system [14][15][16], showing a minimal output performance peak at a moderate optimal noise intensity.…”

“…In addition to the commonly used amplitude noise, our method consisted in using the, usually overlooked, phase noise [25,26]. Moreover, we used a colored noise with a finite autocorrelation time (c ≠ 0) [17,21,22,[27][28][29][30][31], instead of the conventional quasi-white noise (c ≈ 0) [2][3][4][5][6][7][8][9][10][11][12][13]27].…”

Control of stochastic and inverse stochastic resonances in a liquid-crystal electroconvection system using amplitude and phase noises

“…Since Benzi et al . first suggested this phenomenon and its underlying mechanism in a study on ice-age cycles 2 , 3 , SR has been extensively investigated in various fields, including physics 4 , 5 , chemistry 6 , 7 , biology 8 , 9 , information technology 10 , 11 , and brain science 12 , 13 . By contrast, an opposing phenomenon known as the inverse SR (ISR) was initially discovered in a neural system 14 – 16 , showing a minimal output performance peak at a moderate optimal noise intensity.…”