Adaptive Wavelets for Signal Analysis
نویسندگان
چکیده
Construction of higher multiplicity wavelets adapted to a particular task is discussed. The proposed method uses parameterization of wavelet matrices. Large classes of wavelet matrices are searched to minimize a given cost function on training data. The method is applied to a problem of detecting and possibly removing a disturbance of a certain kind from a signal. The importance of choosing the right cost function is demonstrated. It is shown that higher multiplicity wavelets adapted to this task are clearly superior to wavelets packets using Daubechies wavelets.
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