Title :
Transient electromagnetic modeling using recurrent neural networks
Author :
Sharma, Hitaish ; Zhang, Q.J.
Author_Institution :
Dept. of Electron., Carleton Univ., Ottawa, Ont., Canada
Abstract :
A novel technique for modeling the behaviour of two port passive electromagnetic (EM) structures with respect to geometrical and material parameters is introduced. A direct time domain (TD) formulation is proposed that utilizes transient responses of the structure to applied excitation signals as training data for recurrent neural networks (RNN). These EM responses are obtainable from TD EM simulators. Once trained, the RNN macromodel can be inserted into circuit simulators for use in circuit analysis. The RNN macromodel is demonstrated with two examples.
Keywords :
circuit simulation; computational electromagnetics; electronic design automation; learning (artificial intelligence); recurrent neural nets; time-domain analysis; transient analysis; two-port networks; RNN macromodel; circuit analysis; circuit simulators; design automation; direct time domain formulation; electromagnetic transient analysis; recurrent neural networks; transient electromagnetic modeling; transient response; two port passive electromagnetic structures; Circuit simulation; Computational modeling; Design automation; Electromagnetic modeling; Electromagnetic transients; Neural networks; Power system transients; Recurrent neural networks; Solid modeling; Training data;
Conference_Titel :
Microwave Symposium Digest, 2005 IEEE MTT-S International
Print_ISBN :
0-7803-8845-3
DOI :
10.1109/MWSYM.2005.1517009