| URN |
etd-0726105-011342 |
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| Author |
Yung-Chen Chou |
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| Author's Email Address |
M923010072@student.nsysu.edu.tw |
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| Statistics |
This thesis had been viewed 4364 times. Download 10 times. |
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| Department |
Electrical Engineering |
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| Year |
2004 |
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| Semester |
2 |
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| Degree |
Master |
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| Type of Document |
|
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| Language |
zh-TW.Big5 Chinese |
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| Title |
Incorporation of Finite Impulse Response Neural Network into the FDTD Method |
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| Date of Defense |
2005-07-19 |
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| Page Count |
87 |
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| Keyword |
Finite-Difference Time Domain
artificial neural networks
Finite Impulse Response Neural Networks
|
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| Abstract |
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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| Advisory Committee |
Tzyy-Sheng Horng - chair
Tzong-Lin Wu - co-chair
Ken-Huang Lin - co-chair
Ming-Cheng Liang - co-chair
Chih-Wen Kuo - advisor
|
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| Files |
indicate in-campus access in a year and off_campus not accessible |
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| Date of Submission |
2005-07-26 |
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