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On the LFM signal improvement by piecewise vibrational resonance using a new spectral amplification factor
dc.contributor.authorJia, Pengxiang
dc.contributor.authorYang, Jianhua
dc.contributor.authorZhang, Xin
dc.contributor.authorSanjuán, Miguel A.f.
dc.date.accessioned2021-01-05T18:44:47Z
dc.date.available2021-01-05T18:44:47Z
dc.date.issued2019-02
dc.identifier.citationJia, Pengxiang; Yang, Jianhua; Zhang, Xin; Sanjuán, Miguel A.f. (2019). "On the LFM signal improvement by piecewise vibrational resonance using a new spectral amplification factor." IET Signal Processing 13(1): 65-69.
dc.identifier.issn1751-9683
dc.identifier.issn1751-9683
dc.identifier.urihttps://hdl.handle.net/2027.42/163797
dc.publisherThe Institution of Engineering and Technology
dc.publisherWiley Periodicals, Inc.
dc.subject.otheroptimal VR phenomenon
dc.subject.otherfrequency modulated signals
dc.subject.otherLFM signal improvement
dc.subject.otherspectral amplification factor
dc.subject.otherpiecewise vibrational resonance method
dc.subject.otheraperiodic VR
dc.subject.otherB0240Z Other topics in statistics
dc.subject.otherB0290Z Other numerical methods
dc.subject.otherB6140 Signal processing and detection
dc.subject.otherC1140Z Other topics in statistics
dc.subject.otherC1260S Signal processing theory
dc.subject.otherC4190 Other numerical methods
dc.subject.othertwice sampling methods
dc.subject.otherpiecewise linear techniques
dc.subject.otherfrequency modulation
dc.subject.otherresonance
dc.subject.othernumerical analysis
dc.subject.otherstochastic processes
dc.subject.othercorrelation methods
dc.subject.othersignal sampling
dc.subject.otherspectrum amplification factor
dc.titleOn the LFM signal improvement by piecewise vibrational resonance using a new spectral amplification factor
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelElectrical Engineering
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/163797/1/sil2bf00702.pdf
dc.identifier.doi10.1049/iet-spr.2018.5101
dc.identifier.sourceIET Signal Processing
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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