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