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Fuh, K.H. and Wang, S.B. (1997) Force Modeling and Forecasting in Creep Feed Grinding Using Improved BP Neural Network. International Journal of Machine Tools and Manufacture, 37, 1167-1178.
https://doi.org/10.1016/S0890-6955(96)00012-0

has been cited by the following article:

• TITLE: Study on the Classification of Pulse Signal Based on the BP Neural Network

  AUTHORS: Shaohua Wang, Jianli Jiang, Xiaobing Lu

  KEYWORDS: BP Neural Network, Pulse Signal, Classification, Dimensional Analysis

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.8 No.5, May 8, 2020

  ABSTRACT: The objectification of the pulse signal analysis is a practical problem. The classification of the pulse signal is studied based on the BP neural network. It is first analyzed how to select the characteristic factors of the pulse signal. Then the method of nondimensionalization/normalization on the pulse signal is presented to preprocess the characteristic factors. The classification of the pulse signal and the effects of the selection of characteristic factors are studied by using the normalized data and BP neural network. It is shown that nondimensionalization/normalization of the data is in favor of the training and forecasting of the network. The selection of characteristic factors affects the accuracy of forecasting obviously. The results of forecasting by selection of 8, 6 and 4 factors respectively show that the less the factors are, the worse the effects are.