Abstract
Stochastic resonance (SR) is an ingenious phenomenon observed in nature and in biological systems but has seen very few practical applications in engineering. It has been observed and analyzed in widely different natural phenomenon including in bio-organisms (e.g. Mechanoreceptor of crayfish) and in environmental sciences (e.g. the periodic occurrence of ice ages). The main idea behind SR seems quite unorthodox – it proposes that noise, that is intrinsically present in a system or is extrinsically added, can help enhance the signal power at the output, in a desired frequency range. Despite its promise and ubiquitous presence in nature, SR has not been successively harnessed in engineering applications. In this work, we demonstrate both experimentally as well as theoretically how the intrinsic threshold noise of an insulator-metal-transition (IMT) material can enable SR. We borrow inspiration from natural systems which use SR to detect and amplify low-amplitude signals, to demonstrate how a simple electrical circuit which uses an IMT device can exploit SR in engineering applications. We explore two such applications: one of them utilizes noise to correctly transmit signals corresponding to different vowel sounds akin to auditory nerves, without amplifying the amplitude of the input audio sound. This finds applications in cochlear implants where ultra-low power consumption is a primary requirement. The second application leverages the frequency response of SR, where the loss of resonance at out-of-band frequencies is used. We demonstrate how to provide frequency selectivity by tuning an extrinsically added noise to the system.
Highlights
Noise is an omnipresent yet unwanted characteristic of all natural systems
The lower limit of the noise variance comes from the fact that at lower values of the noise power, the system does not have enough energy to overcome the potential barrier and make spontaneous transitions
Much like the previous case, the noise power should be bounded to avoid being stuck in the stable state and prevent spontaneous spike generation uncorrelated with the input
Summary
Noise is an omnipresent yet unwanted characteristic of all natural systems. Since we cannot eliminate noise from useful signals, the commonly used engineering technique is to have a stochastic estimate of the noise and design engineering solutions that can improve the signal-to-noise ratio and reduce the overall impact of noise. Classical SR requires three main components, namely a bi-stable potential-well system (Fig. 1A), a weak signal whose power is insufficient to make the transition from one well to another and a noise source which enables the signal to overcome this potential barrier and make spontaneous transitions[17]. If the value of A is less that what is required to cross the potential barrier the system will stay at one of the stable states without any external influence It has been shown[6] that if the noise variance is in a certain range (η1, η2), the output oscillates between −1 and +1 at the frequency of the signal. The second type of stochastic resonance does not require a bi-stable system Instead it requires an excitable system with a thresholding mechanism, where if the input crosses a certain value we record one event such as a spike at the output (Fig. 1B). The term SR has been used by authors in linear systems where the output of the system varies as a function of some particular characteristics of the noise21. shows and calculates SR in case of linear sustems with multiplicative noise where the SNR of the system exhibit extrema as the noise correlation time and asymmetry changes
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