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Unified Wavelet Transform Analysis Adapted to Different Biomedical Applications
Abstract
In biomedical signal processing, wavelet transform has gained an edge over other existing methods due to its highly efficient transforming capabilities. Relative wavelet energy is a technique used to extract meaningful and concise information from wavelet coefficients for signal classification. The possibility of classifying large datasets combined with the simplicity of the process makes this technique very attractive for many applications. The focus is on testing and validating the use of this technique on different signals keeping in view the specific needs for various biomedical applications. The importance of this unified technique is highlighted with statistical results and validation on several benchmark datasets.
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