wavelet
- noun
- /ˈweɪvlɪt/
- Specialized
- The wavelet is a crucial tool for analyzing signals across different scales in data processing.
- wavelet transform
- Discrete wavelet
- Complex wavelet
Examples
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The spectral and wavelet analysis diagrams of the Fe/K display distinct power in the precession frequency band.
Academic text (2018) -
Therefore, many researchers have attempted to achieve better fusion results using discrete wavelet transform (DWT) 28, 29, 32.
Academic text (2016) -
All these characteristics and attributes make the wavelet transform a very attractive tool in any automated vision or object recognition problem.
Academic text (1995) -
Several approaches with this purpose include the implementation of frequency and time domain filters, like wavelet thresholding techniques 2-6.
Academic text (2017) -
Another recent recourse to the problem of feature extraction involves the application of wavelet theory (5-8).
Academic text (1995) -
To obtain more information, the wavelet modulus maxima method for physiologic time series was adapted.
Blog text (10) -
The proposed method applies a Gabor Wavelet transform to the gastric X-ray image in eight individual directions.
Academic text (2016) -
Two-dimensional rotated complex wavelet filters are designed to extract features from source modalities that represent features in twelve different directions.
Academic text (2016) -
Brunton et al. (2011) adopt wavelet bases to model independent prior distributions at multiple scales for the 3D facial shape.
Academic text (2018) -
Wavelet-based methods are much superior to pyramid transforms due to their better spatiospectral localization.
Academic text (2016)
Surface Forms
Morphology
Etymology
Wavelet comes from wave plus the ending -let meaning 'small', just like booklet; in math a wavelet is a 'small wave' shape used to analyze signals or data at different sizes, so the name shows it is a little wave that helps study information.