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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84734完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 鄭宇翔(Yu-Hsiang Cheng) | |
| dc.contributor.author | Chu-Hsuan Lin | en |
| dc.contributor.author | 林楚軒 | zh_TW |
| dc.date.accessioned | 2023-03-19T22:22:53Z | - |
| dc.date.copyright | 2022-09-19 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-09-05 | |
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84734 | - |
| dc.description.abstract | 本論文旨在研究太赫茲波導濾波器的設計，並採用電腦數值控制銑削技術製造出波導濾波器，最後通過量測結果以證明設計的可行性。本論文主要分為兩部分。第一部分是濾波器的基本理論。在本節中吾人分別以耦合矩陣理論與阻抗轉換器理論設計兩個工作於WR-3頻段(220 – 330 GHz)的非對稱電感性虹膜耦合的6階柴比雪夫波導濾波器。第一個濾波器的中心頻率為300 GHz，比例頻寬為13.3%；第二個則是基於IEEE 802.15.3d標準中的CH67 (278.64 – 304.56 GHz)所訂定。而第二部分則是人工智慧。在此節中吾人由訓練完成的人工神經網路來獲得所目標響應下的濾波器幾何尺寸。並且為了進一步提高其訓練速率，吾人先將濾波器的頻率響應做向量擬合以轉為對應的極點與殘值進而減少網路輸入個數。訓練結果表明濾波器尺寸的均方誤差接近電腦數值控製銑削的製作誤差。 量測結果表明300 GHz波導濾波器其在281 – 324 GHz的通帶內穿透損耗小於5 dB，反損耗優於13 dB。CH67濾波器在276 – 310 GHz的通帶內穿透損耗小於3 dB，反損耗優於17 dB。由於這兩個濾波器的性能並不完美，所以吾人作了後模擬以分析探討影響通帶內的穿透損耗的原因，以便在後續的設計中進行修正與改進。 | zh_TW |
| dc.description.abstract | The purpose of this thesis is to study terahertz waveguide filter designs. The designed waveguide filters are fabricated by the computer numerical controlled milling process and then measured to show the feasibility. The thesis is mainly divided in to two parts. The first part is the basic theory of the microwave filters. In this section, two asymmetric inductive iris coupled waveguide bandpass filters with 6-pole Chebyshev responses are designed by coupling matrix theory and impedance inverter theory, respectively. The first filter has a center frequency of 300 GHz and a fractional bandwidth of 13.3%; the second filter is designed to apply to Channel 67 of the IEEE 802.15.3d standard (278.64 – 304.56 GHz). The second part is the application of artificial intelligence to filter designs. In this section, an artificial neural network is used to provide the filter geometries using the desired frequency response. In order to improve the training speed, we first use the vector fitting technique to convert the frequency response into the corresponding poles and residues so that we can reduce the number of the network inputs. The results show that the mean squared error of the filter dimensions is close to the fabricating error of computer numerical controlled milling process. The measurement results show that the insertion loss of the 300 GHz filter is less than 5 dB and the return loss is better than 13 dB in the range 281 – 324 GHz. The insertion loss of the CH67 filter is less than 3 dB and the return loss is better than 17 dB in the range 276 – 310 GHz. Since the performances of these two filters are not perfect, I perform the post-simulation to analyze the causes of the insertion loss in the passband, in order to improve our future designs. | en |
| dc.description.provenance | Made available in DSpace on 2023-03-19T22:22:53Z (GMT). No. of bitstreams: 1 U0001-0308202215533900.pdf: 7328416 bytes, checksum: ac6629d6cddb087dc54577066473f4e2 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 口試委員會審定書 # 誌謝 i 中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vii LIST OF TABLES xii Chapter 1 簡介 1 1.1 太赫茲輻射與應用概述 1 1.2 太赫茲波導和微加工概述 3 1.3 論文動機和目標 4 1.4 章節與內容概述 5 Chapter 2 耦合共振濾波器和矩形波導基本理論 6 2.1 雙埠濾波器概述 6 2.2 濾波器轉移函數 7 2.2.1 巴特沃茲響應 7 2.2.2 柴比雪夫響應 8 2.2.3 低通到帶通的轉換 9 2.2.4 導抗轉換器 11 2.3 共振濾波器耦合矩陣理論 13 2.3.1 等效電路迴圈方程式 13 2.3.2 等效電路節點方程式 16 2.3.3 通用耦合矩陣的合成 18 2.3.4 耦合共振濾波器示例 19 2.4 波導濾波器的物理實現 21 2.4.1 矩形波導與共振腔 21 2.4.2 虹膜耦合結構 25 2.4.3 電感與電容性虹膜耦合波導濾波器的頻率選擇度討論 26 2.4.4 物理結構的外部品質因子萃取 28 2.4.5 物理結構的共振腔間的耦合係數萃取 29 2.4.6 阻抗轉換器模型 32 2.5 濾波器優化 37 Chapter 3 基於人工神經網路的濾波器優化 38 3.1 應用人工神經網路於射頻微波領域 38 3.1.1 多層感知器網路 38 3.1.2 神經元激活函數 40 3.1.3 反向傳播演算法 41 3.1.4 共軛梯度演算法 43 3.2 Vector Fitting technology 44 3.2.1 Vector Fitting 演算法 44 3.2.2 應用Vector Fitting 近似濾波器頻率響應 46 3.3 神經網路輔助優化帶通濾波器 48 3.3.1 神經網路模型架構 48 3.3.2 神經網路的訓練與評估 50 Chapter 4 波導濾波器實作與量測討論 56 4.1 CNC 銑削技術 56 4.2 300 GHz 波導濾波器的設計與製作 56 4.3 300 GHz 波導濾波器的量測分析與討論 59 4.4 CH67波導濾波器的設計與製作 64 4.5 CH67波導濾波器的量測分析與討論 66 Chapter 5 結論 76 REFERENCE 77 | |
| dc.language.iso | zh-TW | |
| dc.subject | 太赫茲 | zh_TW |
| dc.subject | 人工神經網路 | zh_TW |
| dc.subject | 波導濾波器 | zh_TW |
| dc.subject | terahertz | en |
| dc.subject | waveguide bandpass filter | en |
| dc.subject | artificial neural network | en |
| dc.title | 基於人工神經網路的太赫茲波導帶通濾波器設計 | zh_TW |
| dc.title | Terahertz Waveguide Bandpass Filter Designs Using an Artificial Neural Network | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 110-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 吳宗霖(Tzong-Lin Wu),陳士元(Shih-Yuan Chen),馬自莊(Tzyh-Ghuang Ma) | |
| dc.subject.keyword | 太赫茲,波導濾波器,人工神經網路, | zh_TW |
| dc.subject.keyword | terahertz,waveguide bandpass filter,artificial neural network, | en |
| dc.relation.page | 82 | |
| dc.identifier.doi | 10.6342/NTU202202015 | |
| dc.rights.note | 同意授權(限校園內公開) | |
| dc.date.accepted | 2022-09-06 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電信工程學研究所 | zh_TW |
| dc.date.embargo-lift | 2022-09-19 | - |
| 顯示於系所單位： | 電信工程學研究所 | |
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