Wavelet transforms are mathematical techniques used to analyze and represent signals and functions in a way that provides both time and frequency information. Unlike traditional Fourier transforms that use sine and cosine functions, wavelet transforms utilize short waveforms called wavelets, which can be scaled and shifted, allowing for a more localized analysis of signals. This flexibility makes wavelet transforms particularly useful for processing non-stationary signals, which change over time.
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