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
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...
In [67], a fault diagnosis method for the open-transistor faults of power semiconductors was proposed based on multilevel signal decomposition and reconstruction of three-phase grid-connected inverter currents using an artificial neural network (ANN) and multiresolution analysis (MRA). A similar ...