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- W1980260577 abstract "A successive least-squares approach is proposed to find an optimal model of a flat neural network in a short period of time. It is based on a minimum description length (MDL) neural network that uses the MDL principle as the stopping criterion. Different from conventional algorithms on flat neural networks that apply least-squares technique on weights between hidden layer and output layer only, it extends the least-squares technique to weights between the input layer and the hidden layer. We apply this algorithm to the chaotic Mackey-Glass time series and chaotic laser time series. The results show that it provides satisfactory prediction within a small amount of time." @default.
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- W1980260577 date "2004-08-23" @default.
- W1980260577 modified "2023-09-26" @default.
- W1980260577 title "Successive-least-squares error algorithm on minimum description length neural networks for time series prediction" @default.
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- W1980260577 doi "https://doi.org/10.1109/icpr.2004.871" @default.
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