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|Title:||Binary signal transmission in nonlinear sensors: stochastic resonance and human hand balance|
|Citation:||IEEE Instrumentation and Measurement Magazine, 2020; 23(1):44-49|
|Fabing Duan, Lingling Duan, François Chapeau-Blondeau, Yuhao Ren, and Derek Abbott|
|Abstract:||Many sensors exhibit nonlinear characteristics - and are deployed in noisy environments -. In terms of device design and forming standards, this is a challenging area. However, it also presents opportunities for non-conventional signal processing methods based on stochastic resonance that have been shown to be of benefit for individual nonlinear sensors -, sensor arrays -, sensor networks , , , and even portable devices for people with reduced sensory capacity -. The most fascinating property of stochastic resonance is that nonlinear sensors connected in parallel or in a network yield improved performance over that achieved by using individual sensors -. Studies in stochastic resonance have led to evidence of noise-enhanced signal transmission and processing in nonlinear sensors, and noise can be exploited in the design of engineered devices -,  and biological systems , -. This paper studies noise-enhanced signal transmission and processing in nonlinear sensors and also exploits the positive role of noise in the design of engineered devices that enhance the sensitivity of hand movements.|
|Keywords:||Sensor arrays; noise level; vibrations; neurons; Hopfield neural networks; sensor phenomena and characterization|
|Rights:||© 2020 IEEE|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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