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- W2279873318 abstract "Information overload has resulted in difficulties of managing and processinginformation. Reduction of data using well-defined techniques such as rough set mayprovide a means to overcome this problem. Extracting useful imformation and knowledge from data is a major concern in information science. Artificial intelligence systems, such as neural network systems, are widely used to extract andinfer knowledge from databases. This study explored the training of a neural network inference system using theextended Kalman filter (EKF) learning algorithm. The inference accuracy, inference duration and training performance of this extended Kalman filter neural networkwere compared with the standard back-propagation algorithm and an improved version of the back-propagation neural network learning algorithm. It wasdiscovered that the extended Kalman filter trained neural network required less" @default.
- W2279873318 created "2016-06-24" @default.
- W2279873318 creator A5064078094 @default.
- W2279873318 date "2005-04-01" @default.
- W2279873318 modified "2023-09-27" @default.
- W2279873318 title "An Improvement on Extended Kalman Filter for Neural Network Training" @default.
- W2279873318 hasPublicationYear "2005" @default.
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