… We start with the brief review of 1-D wavelet transform. The wavelet transform is defined
as a decomposition of a signal f (t) with a family of real orthonormal bases ψ j,k (t) generated …

… of the continuous wavelet transform properties and define characteristic functions to detect
P‐ … In addition, the algorithms automatically adapt to the characteristics of the arrival to treat …

… This work deals with the automatic detection of focal EEG signals. Figures 5 and 6 are
typical RPS plot of rhythms of focal and non-focal EEG signals, respectively. The circles …

… In the last three decades, the development of methods for the automatic detection of seismic
… The current stage in the construction of methods for the automatic detection of seismic …

… adaptive whitening filter and the wavelet transform used to detect the abrupt changes in the
… , the automatic segmentation based on abrupt change detection using the wavelet transform …

… In wavelet analysis, wavelet transform of a signal is the projection of the signal onto the
shifted and scaled version of mother wavelet. 'Its scale is representation of its frequency …

… Thus, there is an urgent need to automatically detect spikes and seizures. In addition, the use
of … Multiscale representation of wavelet transforms of a spike and wave complex (a), and an …

… patterns based on discrete Wavelet transform are studied for detection and identification of
both… The Wavelet function Daubichies4 is used as basefunction in detection and identification …

… wavelet transform (CWT)-based peak detection algorithm has been devised that identifies
peaks with different scales and amplitudes. By transforming the spectrum into wavelet space, …

… Abstract—In this article, we propose an automatic method to detect microaneurysms in retina
photographs. Microaneurysms are the most frequent and usually the first lesions to appear …