Low power domain-specific reconfigurable array for discrete wavelet transforms targeting multimedia applications

2005 ◽  
Author(s):  
S. Baloch ◽  
I. Ahmed ◽  
T. Arslan ◽  
A. Stoica
Keyword(s):  
Low Power ◽  
Wavelet Transforms ◽  
Multimedia Applications ◽  
Discrete Wavelet ◽  
Discrete Wavelet Transforms ◽  
Domain Specific ◽  
Power Domain ◽  
Reconfigurable Array

Image Weight Models Based on Discrete Wavelet Transforms

2021 ◽  
Author(s):  
Maya M. Lyasheva ◽  
Stella A. Lyasheva ◽  
Mikhail P. Shleymovich
Keyword(s):  
Wavelet Transforms ◽  
Discrete Wavelet ◽  
Discrete Wavelet Transforms

scholarly journals Gated Recurrent Unit Networks and Discrete Wavelet Transforms Applied to Forecasting and Trading in the Stock Market

2020 ◽  
Author(s):  
Victor Biazon ◽  
Reinaldo Bianchi
Keyword(s):  
Stock Market ◽  
Wavelet Transforms ◽  
Stock Price ◽  
Discrete Wavelet ◽  
Discrete Wavelet Transforms ◽  
Time Step ◽  
Proposed Model ◽  
Gated Recurrent Unit ◽  
Novel Model ◽  
Unit Network

Trading in the stock market always comes with the challenge of deciding the best action to take on each time step. The problem is intensified by the theory that it is not possible to predict stock market time series as all information related to the stock price is already contained in it. In this work we propose a novel model called Discrete Wavelet Transform Gated Recurrent Unit Network (DWT-GRU). The model learns from the data to choose between buying, holding and selling, and when to execute them. The proposed model was compared to other recurrent neural networks, with and without wavelets preprocessing, and the buy and hold strategy. The results shown that the DWT-GRU outperformed all the set baselines in the analysed stocks of the Brazilian stock market.

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