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https://hdl.handle.net/2440/128761
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Type: | Journal article |
Title: | Binary signal transmission in nonlinear sensors: stochastic resonance and human hand balance |
Author: | Duan, F. Duan, L. Chapeau-Blondeau, F. Ren, Y. Abbott, D. |
Citation: | IEEE Instrumentation and Measurement Magazine, 2020; 23(1):44-49 |
Publisher: | IEEE |
Issue Date: | 2020 |
ISSN: | 1094-6969 1941-0123 |
Statement of Responsibility: | Fabing Duan, Lingling Duan, François Chapeau-Blondeau, Yuhao Ren, and Derek Abbott |
Abstract: | Many sensors exhibit nonlinear characteristics [1]-[5] and are deployed in noisy environments [1]-[7]. 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 [1]-[7], sensor arrays [3]-[10], sensor networks [3], [8], [11], and even portable devices for people with reduced sensory capacity [12]-[14]. 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 [1]-[10]. 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 [2]-[7], [10] and biological systems [1], [11]-[13]. 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 |
DOI: | 10.1109/MIM.2020.8979523 |
Published version: | http://dx.doi.org/10.1109/mim.2020.8979523 |
Appears in Collections: | Aurora harvest 4 Electrical and Electronic Engineering publications |
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