Continuous and discrete wavelet transforms 629 phenomena of duration shorter than the time window moreover shortening the win dow to increase time resolution can result in unacceptable increases in computational. In numerical analysis and functional analysis a discrete wavelet transform dwt is any wavelet transform for which the wavelets are discretely sampled as with other wavelet transforms a key advantage it has over fourier transforms is temporal resolution it captures both frequency and location information location in time. In all reality everything on a computer is discrete of course so it seems obvious that discrete wavelets are the right choice for digital signal processing however according to wikipedia it is the continuous wavelet transform that is primarily used in digital image compression as well as a large number of other digital data processing . We need to shift the wavelet to align with the feature we are looking for in a signalthe two major transforms in wavelet analysis are continuous and discrete wavelet transforms
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