New type of spectral nonlinear resonance enhances identification of weak signals

Some nonlinear systems possess innate capabilities of enhancing weak signal transmissions through a unique process called Stochastic Resonance (SR). However, existing SR mechanism suffers limited signal enhancement from inappropriate entraining signals. Here we propose a new and effective implementa...

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Main Authors: Lin, Rongming, Ng, Teng Yong, Fan, Zheng
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2020
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Online Access:https://hdl.handle.net/10356/142342
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1423422023-03-04T17:21:10Z New type of spectral nonlinear resonance enhances identification of weak signals Lin, Rongming Ng, Teng Yong Fan, Zheng School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Stochastic Resonance (SR) Signal Some nonlinear systems possess innate capabilities of enhancing weak signal transmissions through a unique process called Stochastic Resonance (SR). However, existing SR mechanism suffers limited signal enhancement from inappropriate entraining signals. Here we propose a new and effective implementation, resulting in a new type of spectral resonance similar to SR but capable of achieving orders of magnitude higher signal enhancement than previously reported. By employing entraining frequency in the range of the weak signal, strong spectral resonances can be induced to facilitate nonlinear modulations and intermodulations, thereby strengthening the weak signal. The underlying physical mechanism governing the behavior of spectral resonances is examined, revealing the inherent advantages of the proposed spectral resonances over the existing implementation of SR. Wide range of parameters have been found for the optimal enhancement of any given weak signal and an analytical method is established to estimate these required parameters. A reliable algorithm is also developed for the identifications of weak signals using signal processing techniques. The present work can significantly improve existing SR performances and can have profound practical applications where SR is currently employed for its inherent technological advantages. MOE (Min. of Education, S’pore) Published version 2020-06-19T05:16:25Z 2020-06-19T05:16:25Z 2019 Journal Article Lin, R., Ng, T. Y., & Fan, Z. (2019). New type of spectral nonlinear resonance enhances identification of weak signals. Scientific Reports, 9(1), 14125-. doi:10.1038/s41598-019-50767-z 2045-2322 https://hdl.handle.net/10356/142342 10.1038/s41598-019-50767-z 31575962 2-s2.0-85072847851 1 9 en Scientific Reports © 2019 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Te images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Stochastic Resonance (SR)
Signal
spellingShingle Engineering::Mechanical engineering
Stochastic Resonance (SR)
Signal
Lin, Rongming
Ng, Teng Yong
Fan, Zheng
New type of spectral nonlinear resonance enhances identification of weak signals
description Some nonlinear systems possess innate capabilities of enhancing weak signal transmissions through a unique process called Stochastic Resonance (SR). However, existing SR mechanism suffers limited signal enhancement from inappropriate entraining signals. Here we propose a new and effective implementation, resulting in a new type of spectral resonance similar to SR but capable of achieving orders of magnitude higher signal enhancement than previously reported. By employing entraining frequency in the range of the weak signal, strong spectral resonances can be induced to facilitate nonlinear modulations and intermodulations, thereby strengthening the weak signal. The underlying physical mechanism governing the behavior of spectral resonances is examined, revealing the inherent advantages of the proposed spectral resonances over the existing implementation of SR. Wide range of parameters have been found for the optimal enhancement of any given weak signal and an analytical method is established to estimate these required parameters. A reliable algorithm is also developed for the identifications of weak signals using signal processing techniques. The present work can significantly improve existing SR performances and can have profound practical applications where SR is currently employed for its inherent technological advantages.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Lin, Rongming
Ng, Teng Yong
Fan, Zheng
format Article
author Lin, Rongming
Ng, Teng Yong
Fan, Zheng
author_sort Lin, Rongming
title New type of spectral nonlinear resonance enhances identification of weak signals
title_short New type of spectral nonlinear resonance enhances identification of weak signals
title_full New type of spectral nonlinear resonance enhances identification of weak signals
title_fullStr New type of spectral nonlinear resonance enhances identification of weak signals
title_full_unstemmed New type of spectral nonlinear resonance enhances identification of weak signals
title_sort new type of spectral nonlinear resonance enhances identification of weak signals
publishDate 2020
url https://hdl.handle.net/10356/142342
_version_ 1759853753408684032