DocumentCode
2733770
Title
A Recurrent Neural Networks Based Modeling Approach for Internal Circuits of Electronic Devices
Author
Aimin, Zhang ; Hang, Zhang ; Hong, Li ; Degui, Chen
Author_Institution
Sch. of Electron. & Inf. Eng., Xi´´an Jiaotong Univ., Xi´´an
fYear
2009
fDate
12-16 Jan. 2009
Firstpage
293
Lastpage
296
Abstract
In this paper, a modeling approach is developed for internal circuits of electronic devices. Two types of recurrent neural networks (RNN), both with and without time sequence, are trained to learn the dynamic responses of interferences in frequency and time domain respectively. After training, the RNN model provides fast evaluation of interference responses of the original internal circuits, which is useful for electromagnetic susceptibility (EMS) analysis and optimization of electronic devices. Two examples are provided to demonstrate the validity of the proposed modeling approach.
Keywords
electromagnetic interference; recurrent neural nets; electromagnetic susceptibility; electronic devices; interference responses; internal circuits; modeling approach; recurrent neural networks; Circuit simulation; Electromagnetic analysis; Electromagnetic interference; Electromagnetic modeling; Frequency domain analysis; Industrial electronics; Medical services; Power system modeling; Recurrent neural networks; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Electromagnetic Compatibility, 2009 20th International Zurich Symposium on
Conference_Location
Zurich
Print_ISBN
978-3-9523286-4-4
Type
conf
DOI
10.1109/EMCZUR.2009.4783448
Filename
4783448
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