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Combination of Infinite Impulse Response Neural Networks and the FDTD Method in Signal Prediction

The Finite-Difference Time-Domain Method (FDTD) is a very powerful numerical method for the full wave analysis electromagnetic phenomena. Due to its flexibility, it can be used to solve numerous electromagnetic scattering problems on microwave circuits, dielectrics, and electromagnetic absorption in biological tissue at microwave frequencies.
However, it needs so much computation time to simulate microwave integral circuits by applying the FDTD method. If the structure we simulated is complicated and we want to obtain accurate frequency domain scattering parameters, the simulation time will be so much longer that the efficiency of simulation will be bad as well. Therefore, in the thesis, we introduce an artificial neural networks (ANN) method called ¡§Infinite Impulse Response Neural Networks (IIRNN)¡¨ can speed up the FDTD simulation time. In order to boost the efficiency of the FDTD simulation time by stopping the simulation after a sufficient number of time steps and using FIRNN as a predictor to predict time series signal.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0111107-223732
Date11 January 2007
CreatorsChen, Jiun-Kai
ContributorsTzyy-Sheng Horng, Ken-Huang Lin, Chih-Wen Kuo
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0111107-223732
Rightsnot_available, Copyright information available at source archive

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