Abstract
This article reports early results on digital implementation of first- and nth-order hyperbolic wavelets whose important parameters are explicitly expressed and numerically estimated. The first-order hyperbolic, Morlet and Choi-Williams wavelets are compared in detail by numerically calculating their band-peak frequencies, minimum numbers of sampling points, scale resolutions, and maximum numbers of scales. One of the main aims is to show that there exists a strong link among time-frequency kernels and wavelets. This relationship helps to expand and link time-frequency and wavelet approaches to signal analysis. One example of using the hyperbolic wavelet for speech recognition is also given.
Original language | English |
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Pages (from-to) | 4678-4693 |
Number of pages | 16 |
Journal | Review of Scientific Instruments |
Volume | 75 |
Issue number | 11 |
DOIs | |
Publication status | Published - 2004 |
Keywords
- kernel functions
- signal processing
- wavelets (mathematics)