The invention is directed to denoising techniques for electrograms, or other biomedical signals, in which wavelet transformations are used in the denoising process. For example, an electrogram can be represented by a finite set of wavelets which comprise a decomposition of the electrogram in the scale-time domain. In accordance with the invention, an electrogram can be transformed into a set of wavelets, and thresholding can be performed on the wavelets to eliminate noise while preserving the information of the electrogram. Different thresholds can be used for the wavelets in different scales for improved denoising results. If a respective threshold exceeds a wavelet coefficient, the wavelet coefficient is reduced. Following the thresholding process, the wavelets can be converted into a denoised electrogram, which can be analyzed or processed. In this manner, wavelet transformations can be exploited for effective electrogram denoising.
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