SSNF Denoising Algorithm Based on Wavelet Transform Inter-Scale Correlation
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This is the SSNF algorithm I downloaded, which is a denoising algorithm based on inter-scale correlation in wavelet transform. This algorithm serves as an effective signal processing method that helps remove noise from signals and enhance signal quality. Through wavelet decomposition of signals and utilization of correlations between different scales, the SSNF algorithm can accurately identify and eliminate noise components. The core implementation typically involves multi-level wavelet decomposition using functions like wavedec(), followed by correlation analysis between adjacent scales to distinguish noise from true signal components. This process enables us to obtain cleaner, more accurate signals, thereby facilitating better subsequent analysis and processing operations. Key algorithmic steps include thresholding based on inter-scale dependencies and wavelet reconstruction using waverec() function to restore the denoised signal.
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