Using wavelet neural networks for the optimal design of electromagnetic devices

Autor:	Yang Qingxin, Yan Weili, Shen Xueqin, Wu Qing
Rok vydání:	1997
Předmět:	Optimal design Nonlinear system Probabilistic neural network Computer science Control theory Wavelet transform Feedforward neural network Cascade algorithm Electrical and Electronic Engineering Computer Science::Databases Electronic Optical and Magnetic Materials
Zdroj:	IEEE Transactions on Magnetics. 33:1928-1930
ISSN:	0018-9464
Popis:	A feedforward neural network based on the wavelet transform which can be applied to the approximation of complex nonlinear functions is discussed. A wavelet neural network can establish an exact model through a self-adaptive procedure by learning input/output maps from the training sets which are generated by finite element analysis. The structure of the network can be definitely developed, and the learning speed is increased. We have applied it to the optimization design of an AC vacuum contactor with a DC exciting electrical circuit and obtained a satisfactory scheme.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::801aa8e7c77102f0fa925d4e1c184f13 https://doi.org/10.1109/20.582669 Zobrazit plný text záznamu