Значения термина wavelet transform на английском

Experimental results demonstrate that the proposed algorithm outperforms the popular fusion algorithm based on wavelet transform.

Using a cross- wavelet transform we find a significant out-of-phase relationship between human parainfluenza 3 and temperature and dew point.

Conclusion: This study showed that the wavelet transform could be a useful tool to study the uterine EMG activity.

Continuous wavelet transform (CWT) analysis is another frequency analysis that can show the temporal stability of a frequency.

In this paper, we developed and evaluated a robust single-lead electrocardiogram (ECG) delineation system based on the wavelet transform (WT).

PMID: 29369468 Continuous wavelet transform (CWT) analysis is another frequency analysis that can show the temporal stability of a frequency.

The methodology operates two rotations on the image data, one local using the wavelet transform and one global using the singular value decomposition.

Distributed lag nonlinear models, Pearson's correlation coefficient and wavelet transform coherence were employed to appraise the relationship between meteorological factors and COVID-19 cases.

Conclusions: Discrete wavelet transform allows for an accurate determination of ON and OFF retinal pathways even in ERGs evoked to a short flash.

In this paper, a deep learning framework for detection and classification of EMG signals for diagnosis of neuromuscular disorders is proposed employing cross wavelet transform.

The discrimination is based on the extraction of suitable features from the time-frequency representation of the EEG signals through continuous wavelet transform (CWT).

In this work, a new hybrid algorithm based on the selection of the most informative variables in the continuous wavelet transform (CWT) domain is described.

The primary outcome was the magnitude of the spectral component in the frequency range between .027 and .073 Hz measured with continuous Morlet wavelet transform.

Peak profiles are obtained by a preprocessing based on Continuous Wavelet Transform (CWT), coupled with a machine learning protocol aimed at avoiding selection bias effects.

First, the time course of neural oscillations ranging from theta (4.5 Hz) to gamma (42 Hz) frequencies were identified using single-trial continuous wavelet transforms.