Open AccessJournal Article
Function Approximation Based on Neural Network
3
TL;DR: A learning algorithm is proposed which combines function approximate and neural network model and the function approximate is given as an example to show that the methold can be used practically.
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Abstract: Function aproximate is introduced and a neural network model is presented.A learning algorithm is proposed which combines function approximate and neural network model.The function approximate is given as an example to show that the methold can be used practically.
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Citations
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References
Modeling of switched reluctance motor based on combined clustering RBF network
Suying Zhou
- 01 Aug 2017
TL;DR: Combined clustering RBF neural network is presented as a tool to develop the model of the SRM and results show that the model is reasonable and can reflect the electromagnetic characteristics of the motor.
6
Research on control algorithm for weaving non-equal diameter tubular fabric with constant weft density
Sun Zhi-hong,Li Zhiyao,Zhou Shenhua,Li Xiang +3 more
- 19 Jun 2013
TL;DR: In this paper, a control algorithm of diameter changing and constant weft density for tubular fabric was presented, in which the RBF (Radial Basis Function, RBF) neural network was used to approximate the shape function of tubular fabrics.
Improvement of the Vehicle License Plate Recognition System in the Environment of Rain and Fog
Zhun Wang,Zhenyu Liu +1 more
- 15 Oct 2015
TL;DR: In this paper, a license plate recognition system based on the theory of digital image processing, computer vision and pattern recognition technology is proposed. But the system is not suitable for the environment of rain and fog.