… In light of this, in this paper we propose a wavelet-based neural network structure called
multilevel Wavelet Decomposition Network (mWDN) for building frequency-aware deep learning …

… of wavelet transform (WT) and bidirectional long short term memory (BiLSTM) deep learning
network … number of IMF series by combining the wavelet decomposed components (D1-D6) …

… only use the deep learning neural networks in the wavelet decomposing framework to realize
… to combine the data decomposition algorithm and the deep learning algorithm for the wind …

… DL model based on wavelet decomposition (WD), the Convolutional Neural Network (CNN), …
For certain weather types, the raw solar irradiance sequence is decomposed into several …

… Neural Networks for Deep Learning A convolution neural network of deep learning is a
deep-learning network generated on the theoretical basis of a neural network. The neural …

… Unlike multi-level wavelet decomposition, our multiscale convolutional network is not
guaranteed to extract identical features at multiple scales. This can impact its ability to recognize …

… End-to-end training is performed using the cross-entropy loss function, in combination with
some regularization terms to enforce a wavelet decomposition structure during training. The …

… We limit the scope of this article to the second category, which covers wavelet networks, …
and a wavelet decomposition have been used in so-called wavelet networks. The output of …

… We tested our wavelet decomposition based machine learning approach using the real traffic
… apply wavelet decomposition over the data before feeding to the predictive neural network. …

… The design concept of the DWT-driven FL-Layer was inspired by the multiresolution wavelet
decomposition algorithm in the signal analysis field. When performing frequency analysis …