Wavelet thresholding is a signal processing technique that utilizes wavelet transforms to reduce noise in data by applying a thresholding function to the wavelet coefficients. This method works by transforming the original signal into a wavelet representation, where the significant features of the signal can be distinguished from the noise. By setting certain coefficients to zero based on a defined threshold, it effectively cleans the signal while preserving its essential characteristics.
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