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dc.contributor.authorRizzoni, Giorgio
Sayeed, Akbar M.
Jones, Douglas L.
dc.creatorRizzoni, Giorgio
Sayeed, Akbar M.
Jones, Douglas L.
dc.date.accessioned 2007-10-31T01:01:43Z
dc.date.available 2007-10-31T01:01:43Z
dc.date.issued 1996-01-20
dc.date.submitted 1996-01-20
dc.identifier.citation G. Rizzoni, A. M. Sayeed and D. L. Jones, "Design of Training Data Based Quadratic Detectors with Application to Mechanical Systems," 1996.
dc.identifier.urihttps://hdl.handle.net/1911/20280
dc.description Conference Paper
dc.description.abstract Reliable detection of engine knock is an important issue in the design and maintenance of high performance internal combustion engines. Cost considerations dictate the use of vibration signals, measured at the engine block, for knock detection. Conventional techniques use the energy in a bandpass filtered version of the vibration signal as a measure. However, the low signal-to-noise ratio (SNR) in the vibration measurements significantly degrades the performance of such bandpass energy detectors. In this paper, we explore the design and application of more general quadratic detection procedures, including time-frequency methods, to this challenging problem. We use statistics estimated from labeled training data to design the detectors. Application of our techniques to real data shows that such detectors, by virtue of their flexible structure, improve the effective SNR, thereby substantially improving the detection performance relative to conventional methods.
dc.language.iso eng
dc.subjectsignal to noise ratio
quadratic detection
vibration signals
dc.subject.otherTime Frequency and Spectral Analysis
dc.title Design of Training Data Based Quadratic Detectors with Application to Mechanical Systems
dc.type Conference paper
dc.date.note 2004-01-09
dc.citation.bibtexName inproceedings
dc.date.modified 2004-01-22
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)
dc.subject.keywordsignal to noise ratio
quadratic detection
vibration signals
dc.citation.conferenceName IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1109/ICASSP.1996.544208


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  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1278]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

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