Wavelet thresholding is a technique used in signal processing that involves applying thresholds to wavelet coefficients to reduce noise in data. This method utilizes the wavelet transform, which decomposes a signal into different frequency components, allowing for the selective removal of noise by manipulating the coefficients based on their significance. The goal is to enhance the quality of the signal while preserving important features and structures.
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