A Compact and Power-Efficient Noise Generator for Stochastic Simulations

Zhao, Haixiang; Sarpeshkar, Rahul; Mandal, Soumyajit

doi:10.1109/tcsi.2022.3199561

Cited by 2 publications

(1 citation statement)

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“…The SR is a nonlinear system where the noise source is a primary component to enhance the detection probability of weak signals [13]- [14]. In conventional SR hardware, an electrical circuit-based noise generator [15] has a large area and consumes significant power.…”

Section: Introductionmentioning

confidence: 99%

Effect of Stochastic Resonance on Classification Accuracy of Neural Networks Utilizing Inherent Stochasticity in Threshold Voltage of Ovonic Threshold Switching Device

Choi

Kwak

Lee

et al. 2022

IEEE J. Electron Devices Soc.

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In this study, stochastic resonance (SR) exploits the inherent stochastic characteristics of the OTS threshold voltage to enhance the inference performance of neural networks. First, the threshold switching of the OTS device is characterized, and a signal detection using an OTS device is proposed. Next, we investigate the impact of stochasticity in the threshold voltage on detecting weak signals in the SR system. Finally, by evaluating the inference performance of the artificial neural network, we confirm that the inherent stochasticity can effectively restore the degraded MNIST image in poor visibility conditions in the OTS device. As a result, the recognition accuracy was improved from 10.28% to 95.78% when the stochasticity characteristic was reflected. These results show that stochasticity in the device can improve system performance.

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Section: Introductionmentioning

confidence: 99%