Multilevel Discrete Wavelet Decomposition (MDWD) [26] is a wavelet based discrete signal analysis method, which can extract multilevel time-frequency features from a time series by decomposing the series as low and high frequency sub-series level by level. 解释: 相当于将time series x分解成为i...
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 models for time series analysis. mWDN preserves the advantage of multilevel discrete wavelet decomposition in frequency...
Inspired by the abovementioned, we propose a hybrid deep learning model called mWDN-LSTM, which correctly utilizes the cyclic patterns' information to predict stock price while avoiding the data leakage and alleviating boundary problems. According to the experiments on two different datas...
Automatic depth correction method (mWDN-GRU-DTW) for different types of well logs.This methodology extracts depth sequence and frequency information from well logs.The multi-level wavelet decomposition has been embedded into the neural network.Achieved first position in the 2023 SPWLA PDDA ML Competit...