The illustrated wavelet transform handbook: introductory theory and applications in science, engineering, medicine and finance

By D. Adam. 2004

493 citations recorded by the source corpus.

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Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review (2019, background): “This is due to its capacity of studying a number of concepts such as non-stationarity, multiresolution and approximate decorrelation emerge from wavelet filters [17,18,79,80].”
Epileptic Seizure Classification of EEG Time-Series Using Rational Discrete Short-Time Fourier Transform (2015, background): “This has proved to be a very useful property in many practical applications [30].”
Freeway traffic oscillations : microscopic analysis of formations and propagations using Wavelet Transform (2011, background): “…as defined in (1), is selected in this study because of its similar shape to a typical cycle of traffic oscillation and small Shannon entropy (Addison 2002; Fugal 2009). ψ 1 e (1) where is a scale parameter that governs the dilation and contraction of the wavelet, and is a translation…”
The promise of implementing machine learning in earthquake engineering: A state-of-the-art review (2020, methodology): “Technical background of these soft computing techniques and their combinations with ANNs can be found in relevant studies (Fuller, 1995; Wallen, 2004; Whitley et al., 1990).”