2019
DOI: 10.1016/j.apacoust.2017.12.020
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Multidimensional identification of resonances analysis of strongly nonstationary signals, case study: Diagnostic and condition monitoring of vehicle's suspension system

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Cited by 4 publications
(2 citation statements)
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“…This is due to the large number of articles which used advanced and often very time-consuming mathematical algorithms and signal processing methods. A complex methodology for the multidimensional analysis of nonstationary vibration signals has been presented in [ 42 ]. An even more advanced algorithm for computing the averaged infogram for local damage detection in the presence of non-Gaussian impulsive noise was studied in [ 43 ].…”
Section: Resultsmentioning
confidence: 99%
“…This is due to the large number of articles which used advanced and often very time-consuming mathematical algorithms and signal processing methods. A complex methodology for the multidimensional analysis of nonstationary vibration signals has been presented in [ 42 ]. An even more advanced algorithm for computing the averaged infogram for local damage detection in the presence of non-Gaussian impulsive noise was studied in [ 43 ].…”
Section: Resultsmentioning
confidence: 99%
“…At present, the main methods used to predict chaotic time series are the global domain method, local method, adding-weight one-rank local-region method, and maximum Lyapunov exponent prediction method. [10][11][12][13][14]…”
Section: Nonlinear Time Series Predictionmentioning
confidence: 99%