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In the last few decades, methods based on wavelet basis functions have been used abruptly.
The proposed algorithm and CS image-fusion algorithm based on wavelet basis are employed to test the fusion results.
Zainuddin et al. investigated the use of wavelet neural networks (WNNs) based on wavelet basis functions for seizure detection[40].
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Many existing CAD methods rely on fixed basis functions based on wavelet decompositions [1] and Gabor filters [2].
Simulation results have demonstrated significant improvements over wavelet-based methods, namely, TI wavelet denoising, denoising based on wavelet transform footprints, as well as recently introduced EPWT based method.
The WMULDEN is a strategy based on wavelet decomposition.
This method is based on wavelet analysis using the Morlet wavelet and the least mean squares (LMS) adaptive filter.
A new wavelet support vector machine (WN ν-SVM) is proposed based on wavelet theory and modified support vector machine.
Step 2. These images are decomposed into wavelet transformed images, respectively, based on wavelet transformation.
Fig. 5 Reconstruction and decomposition based on wavelet.
De-noising based on wavelet transform footprints [26, 27].
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