Training Recurrent Neural Network Using Multistream Extended Kalman Filter on Multicore Processor and Cuda Enabled Graphic Processor Unit

2009 ◽  
pp. 381-390 ◽  
Author(s):  
Michal Čerňanský
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Recurrent Neural Network ◽  
Multicore Processor ◽  
Graphic Processor Unit ◽  
Graphic Processor ◽  
Processor Unit

scholarly journals Extended Kalman Filter In Recurrent Neural Network: USDIDR Forecasting Case Study

2019 ◽  
Vol 13 (3) ◽  
pp. 293
Author(s):  
Muhammad Asaduddin Hazazi ◽  
Agus Sihabuddin
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Recurrent Neural Network ◽  
Learning Algorithm ◽  
Regularization Parameter ◽  
Training Data ◽  
Stochastic Gradient Descent ◽  
Computational Time ◽  
Currency Exchange

Artificial Neural Networks (ANN) especially Recurrent Neural Network (RNN) have been widely used to predict currency exchange rates. The learning algorithm that is commonly used in ANN is Stochastic Gradient Descent (SGD). One of the advantages of SGD is that the computational time needed is relatively short. But SGD also has weaknesses, including SGD requiring several hyperparameters such as the regularization parameter. Besides that SGD relatively requires a lot of epoch to reach convergence. Extended Kalman Filter (EKF) as a learning algorithm on RNN is used to replace SGD with the hope of a better level of accuracy and convergence rate. This study uses IDR / USD exchange rate data from 31 August 2015 to 29 August 2018 with 70% data as training data and 30% data as test data. This research shows that RNN-EKF produces better convergent speeds and better accuracy compared to RNN-SGD.

scholarly journals Recurrent neural network and extended Kalman filter in SLAM problem

2013 ◽  
Vol 46 (20) ◽  
pp. 23-26 ◽  
Author(s):  
Konstantin Yu. Kotov ◽  
Alexandr S. Maltsev ◽  
Maxim A. Sobolev
Keyword(s):  
Neural Network ◽  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Recurrent Neural Network
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