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A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors
In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR). We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT). Furthermore, we introduce the adaptive filtering scheme to...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756698/ |
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author | Huang, Qi Liu, Jun Li, Hengwei |
author_facet | Huang, Qi Liu, Jun Li, Hengwei |
author_sort | Huang, Qi |
collection | PubMed |
description | In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR). We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT). Furthermore, we introduce the adaptive filtering scheme to realize signal processing automatically. The key of the scheme is how to adjust the barrier height to satisfy the optimal condition of SR in the presence of any input. For the given input signal, we present an operable procedure to execute the adjustment scheme. An example utilizing one audio sensor to detect the fault information from the power supply is given. Simulation results show that the modified stochastic resonance scheme can effectively detect fault signal with strong noise. |
format | Online Article Text |
id | pubmed-3756698 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-37566982013-08-29 A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors Huang, Qi Liu, Jun Li, Hengwei Sensors (Basel) Full Paper In this paper, an approach is presented to detect faint signals with strong noises in sensors by stochastic resonance (SR). We adopt the power spectrum as the evaluation tool of SR, which can be obtained by the fast Fourier transform (FFT). Furthermore, we introduce the adaptive filtering scheme to realize signal processing automatically. The key of the scheme is how to adjust the barrier height to satisfy the optimal condition of SR in the presence of any input. For the given input signal, we present an operable procedure to execute the adjustment scheme. An example utilizing one audio sensor to detect the fault information from the power supply is given. Simulation results show that the modified stochastic resonance scheme can effectively detect fault signal with strong noise. Molecular Diversity Preservation International (MDPI) 2007-02-15 /pmc/articles/PMC3756698/ Text en © 2007 by MDPI (http://www.mdpi.org). Reproduction is permitted for noncommercial purposes. |
spellingShingle | Full Paper Huang, Qi Liu, Jun Li, Hengwei A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors |
title | A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors |
title_full | A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors |
title_fullStr | A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors |
title_full_unstemmed | A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors |
title_short | A Modified Adaptive Stochastic Resonance for Detecting Faint Signal in Sensors |
title_sort | modified adaptive stochastic resonance for detecting faint signal in sensors |
topic | Full Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756698/ |
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