Incorporation of Finite Impulse Response Neural Network into the FDTD Method
碩士 === 國立中山大學 === 電機工程學系研究所 === 93 === 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, dielect...
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ndltd-TW-093NSYS54420852015-12-23T04:08:14Z http://ndltd.ncl.edu.tw/handle/34703736828723907065 Incorporation of Finite Impulse Response Neural Network into the FDTD Method 有限脈衝響應類神經網路與時域有限差分法的結合 Yung-Chen Chou 周昀辰 碩士 國立中山大學 電機工程學系研究所 93 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 “Finite Impulse Response Neural Networks (FIRNN)” 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. Chih-Wen Kuo 郭志文 2005 學位論文 ; thesis 87 zh-TW |
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碩士 === 國立中山大學 === 電機工程學系研究所 === 93 === 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 “Finite Impulse Response Neural Networks (FIRNN)” 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.
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Chih-Wen Kuo |
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Chih-Wen Kuo Yung-Chen Chou 周昀辰 |
author |
Yung-Chen Chou 周昀辰 |
spellingShingle |
Yung-Chen Chou 周昀辰 Incorporation of Finite Impulse Response Neural Network into the FDTD Method |
author_sort |
Yung-Chen Chou |
title |
Incorporation of Finite Impulse Response Neural Network into the FDTD Method |
title_short |
Incorporation of Finite Impulse Response Neural Network into the FDTD Method |
title_full |
Incorporation of Finite Impulse Response Neural Network into the FDTD Method |
title_fullStr |
Incorporation of Finite Impulse Response Neural Network into the FDTD Method |
title_full_unstemmed |
Incorporation of Finite Impulse Response Neural Network into the FDTD Method |
title_sort |
incorporation of finite impulse response neural network into the fdtd method |
publishDate |
2005 |
url |
http://ndltd.ncl.edu.tw/handle/34703736828723907065 |
work_keys_str_mv |
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