Initialization by Selection for Wavelet Network Training

Using the hyperbolic convolution we have constructed the continuous wavelet transform and derived the corresponding admissibility condition.. An example of hyperbolic DOG wavelet

L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des

In this chapter, we propose a generalized lifting-based wavelet processor that can perform various forward and inverse Discrete Wavelet Transforms (DWTs) and Discrete Wavelet

It is adapted to obtain multiple data series at different resolutions by wavelet decomposition and calculate the energy distribution using Parseval’s theorem in order

Since the reflec- tion model used for model-based texture methods is just an approximation, there is a difference between the real image and the image rendered by the reflection

In addition, discrete wavelet transform (DWT) also stimulates particular research interest, since it trans- forms an image into various frequency bands, and natural images often

The conducted experiments show that our hybrid architecture combining wavelet scattering transform and CNN can successfully perform efficient feature extraction for a

The approach consists in appropriately writing the problem in the wavelet domain and then selecting both the block size and threshold parameter at each resolution level by