DocumentCode :
1805780
Title :
Finite element analysis based Hopfield neural network model for solving nonlinear electromagnetic field problems
Author :
Guo, Fei ; Zhang, Peng ; Wang, Fang ; Ma, Xikui ; Qiu, Guanyuan
Author_Institution :
Coll. of Electr. Eng., Xi´´an Jiaotong Univ., China
Volume :
6
fYear :
1999
fDate :
36342
Firstpage :
4399
Abstract :
Based on the finite element method for solving nonlinear magnetic field problems, a locally connected Hopfield network is constructed by taking the energy functional of the boundary value problem as the computing energy function of this neural network. The fact that the steady point of the dynamic system must correspond to the numerical solution of the finite element method is explained explicitly. The numerical results show the effectiveness and correctness of the proposed method
Keywords :
Hopfield neural nets; boundary-value problems; electrical engineering computing; electromagnetic field theory; finite element analysis; Hopfield neural network; boundary value problem; energy function; finite element analysis; nonlinear electromagnetic field; Computer networks; Electromagnetic analysis; Electromagnetic fields; Electromagnetic modeling; Finite element methods; Hopfield neural networks; Magnetic fields; Magnetic flux; Nonlinear magnetics; Saturation magnetization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
ISSN :
1098-7576
Print_ISBN :
0-7803-5529-6
Type :
conf
DOI :
10.1109/IJCNN.1999.830877
Filename :
830877
Link To Document :
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