相控陣列雷達演算法設計 - Algorithm Design for Phased Array Radar
授課教師: 黃彥銘
課程時間:112下-六789
上課地點:
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 40人
課程時間:112下-六789
上課地點:
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
1. 本學期所有課程將會「實體聚集並支援線上會議室同步參與」,連結為 https://ntucc.webex.com/meet/yenminghuang
2. 歡迎所有對相控陣列雷達系統之實務設計和開發有興趣的同學,自在地加入我們的課程社團一起討論和分享,連結為 https://www.facebook.com/groups/ntuphasedarrayradar/
3. 課程投影片將公告並隨時更新於 https://sites.google.com/view/yenming/teaching
4. 歡迎訂閱課程影片youtube頻道: https://www.youtube.com/@ntuphasedarrayradar
5. 由於本課程的時段和形式較為特殊,若有任何問題,請隨時與授課教師聯絡 yenminghuang@ntu.edu.tw
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algorithm design for phased array radar is a graduate-level course designed for students interested in modern radar systems widely used in vehicle networks, surveillance systems, military applications, satellites, etc. this course is the extension of the course entitled signal processing for phased array radar to provide more insights into high-tech radar systems and applications in recent years. from the aspects of digital signal and data processing algorithms with the aid of artificial intelligence (ai), we explore advanced radar technologies.
2. 歡迎所有對相控陣列雷達系統之實務設計和開發有興趣的同學,自在地加入我們的課程社團一起討論和分享,連結為 https://www.facebook.com/groups/ntuphasedarrayradar/
3. 課程投影片將公告並隨時更新於 https://sites.google.com/view/yenming/teaching
4. 歡迎訂閱課程影片youtube頻道: https://www.youtube.com/@ntuphasedarrayradar
5. 由於本課程的時段和形式較為特殊,若有任何問題,請隨時與授課教師聯絡 yenminghuang@ntu.edu.tw
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algorithm design for phased array radar is a graduate-level course designed for students interested in modern radar systems widely used in vehicle networks, surveillance systems, military applications, satellites, etc. this course is the extension of the course entitled signal processing for phased array radar to provide more insights into high-tech radar systems and applications in recent years. from the aspects of digital signal and data processing algorithms with the aid of artificial intelligence (ai), we explore advanced radar technologies.
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 40人
後量子密碼學 - Post-quantum cryptography
授課教師: 楊柏因
課程時間:112下-一234
上課地點: 電二146;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 50人
課程時間:112下-一234
上課地點: 電二146;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
cool 為新版, 請在 ntu cool 查詢資料。
目前量子電腦技術預估可能在10-20年內成熟。未來如果數千量子位元(qubit)的中大型一般用途量子電腦(general purpose quantum computer)問世,將摧毀現今全世界絕大多數廣泛使用的公鑰密碼系統 (pkc, public-key cryptosystem),例如 rsa、diffie-hellman 密鑰交換 (key exchange)、橢圓曲線密碼系統(ecc, elliptic curve cryptosystem)。本課程主要介紹可抵擋量子電腦攻擊的公鑰密碼系統,此一研究方向稱為「後量子密碼學」(pqc, post-quantum cryptography)。
目前量子電腦技術預估可能在10-20年內成熟。未來如果數千量子位元(qubit)的中大型一般用途量子電腦(general purpose quantum computer)問世,將摧毀現今全世界絕大多數廣泛使用的公鑰密碼系統 (pkc, public-key cryptosystem),例如 rsa、diffie-hellman 密鑰交換 (key exchange)、橢圓曲線密碼系統(ecc, elliptic curve cryptosystem)。本課程主要介紹可抵擋量子電腦攻擊的公鑰密碼系統,此一研究方向稱為「後量子密碼學」(pqc, post-quantum cryptography)。
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 50人
信號與系統 - Signals and Systems
信號與系統 - Signals and Systems
授課教師: 楊奕軒
課程時間:112下-一23四7
上課地點: 電二106;電二106;
修課資訊: 【半年】【必修】【2 年級】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項:
課程時間:112下-一23四7
上課地點: 電二106;電二106;
修課資訊: 【半年】【必修】【2 年級】【3學分】
課程概述:
required course for 2nd-year ntu ee students teaching fundamentals of analytical framework to handle continuous-time and discrete-time signals and systems, such as discrete fourier transform, laplace transform and z-transform.
授課資訊: 課程說明 ; 臺大課程網
注意事項:
本課程以英語授課。外系學生加選請於加退選時向授課老師詢問。總人數限 70人限本系所學生(含輔系、雙修生)
信號與系統 - Signals and Systems
計算機結構 - Computer Architecture
計算理論 - Theory of Computing
授課教師: 顏嗣鈞
課程時間:112下-二789
上課地點: 博理112;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 50人
課程時間:112下-二789
上課地點: 博理112;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
this course provides a rigorous, graduate level introduction to automata theory, formal languages, and complexity. topics to be covered will include:
(1). finite automata, regular languages, regular grammars:
deterministic vs. nondeterministic, one-way vs. two-way finite automata, minimization,
pumping lemma for regular sets, closure properties.
(2). pushdown automata, context-free languages, context-free grammars:
deterministic vs. nondeterministic, one-way vs. two-way pdas, reversal bounded pdas,
linear grammars, counter machines, pumping lemma for cfls, chomsky normal form,
greibach normal form, closure properties.
(3). linear bounded automata, context-sensitive languages, context-sensitive grammars.
(4). turing machines, recursively enumerable sets, type 0 grammars:
variants of turing machines, halting problem, undecidability, post correspondence
problem, valid and invalid computations of tms.
(5). basic recursive function theory
(6). basic complexity theory:
various resource bounded complexity classes, including nlogspace, p, np,
pspace, exptime, and many more. reducibility, completeness.
(7). advanced topics in complexity theory:
approximation algorithms, probabilistic complexity, parallel complexity, alternation,
interactive proof systems, oracle computations.
(1). finite automata, regular languages, regular grammars:
deterministic vs. nondeterministic, one-way vs. two-way finite automata, minimization,
pumping lemma for regular sets, closure properties.
(2). pushdown automata, context-free languages, context-free grammars:
deterministic vs. nondeterministic, one-way vs. two-way pdas, reversal bounded pdas,
linear grammars, counter machines, pumping lemma for cfls, chomsky normal form,
greibach normal form, closure properties.
(3). linear bounded automata, context-sensitive languages, context-sensitive grammars.
(4). turing machines, recursively enumerable sets, type 0 grammars:
variants of turing machines, halting problem, undecidability, post correspondence
problem, valid and invalid computations of tms.
(5). basic recursive function theory
(6). basic complexity theory:
various resource bounded complexity classes, including nlogspace, p, np,
pspace, exptime, and many more. reducibility, completeness.
(7). advanced topics in complexity theory:
approximation algorithms, probabilistic complexity, parallel complexity, alternation,
interactive proof systems, oracle computations.
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 50人
計算機模擬 - Computer Simulation
高等數位訊號處理 - Advanced Digital Signal Processing
高等演算法 - Advanced Algorithms
授課教師: 陳和麟
課程時間:112下-五234
上課地點: 明達231;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限180人
課程時間:112下-五234
上課地點: 明達231;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
this course will study various techniques for designing and analyzing algorithms. we will mainly focus on problems for which the exact algorithm is not known or not efficient enough and problems with resource constraints. besides designing efficient algorithms, proving the performance guarantees is also a main topic of this course. some topics that we will cover are as follows:
approximation algorithms: algorithms that find near-optimal solutions with provable performance guarantees in polynomial time. this course will mainly focus on approximation algorithms for np-hard problems.
randomized algorithms: algorithms that use random numbers. we will focus on algorithms with provable success probabilities and good expected solution quality.
the following topics will also be briefly described if time permits.
streaming algorithms: algorithms that solve problems on massive datasets. in this type of problem, usually, the algorithm is only allowed to read the data once and use no more than a constant or poly-logarithmic amount of space.
online algorithm: the input to the problem is not known in advance and arrives over time. an online algorithm must decide how to process a specific input before seeing future inputs. the goal is to perform as well as an algorithm that knows all inputs beforehand.
we will cover algorithm design techniques such as hashing, sampling, and linear programming.
approximation algorithms: algorithms that find near-optimal solutions with provable performance guarantees in polynomial time. this course will mainly focus on approximation algorithms for np-hard problems.
randomized algorithms: algorithms that use random numbers. we will focus on algorithms with provable success probabilities and good expected solution quality.
the following topics will also be briefly described if time permits.
streaming algorithms: algorithms that solve problems on massive datasets. in this type of problem, usually, the algorithm is only allowed to read the data once and use no more than a constant or poly-logarithmic amount of space.
online algorithm: the input to the problem is not known in advance and arrives over time. an online algorithm must decide how to process a specific input before seeing future inputs. the goal is to perform as well as an algorithm that knows all inputs beforehand.
we will cover algorithm design techniques such as hashing, sampling, and linear programming.
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限180人
高等類比積體電路 - Advanced Analog Integrated Circuits
高階系統晶片設計 - Advanced SOC Design
高等電腦視覺 - Advanced Computer Vision
授課教師: 傅楸善
課程時間:112下-二789
上課地點: 資105;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 55人
課程時間:112下-二789
上課地點: 資105;
修課資訊: 【半年】【選修】【碩士班博士班 1,2 年級】【3學分】
課程概述:
內容: 講授高等電腦視覺之基本觀念及立論基礎。
介紹各種高等電腦視覺可能之應用,
並配合各項相關專題課程的需求研發適當之演算法及計算架構並完成軟體模擬。
將涵蓋:
1. 簡介 (introduction),
2. 影像形成 (image formation),
3. 影像處理 (image processing),
4. 模型擬合與最佳化 (model fitting and optimization),
5. 深度學習 (deep learning)
6. 辨認 (recognition)
7. 特徵偵測與配對 (feature detection and matching)
8. 影像對正與縫合 (image alignment and stitching)
9. 運動估計 (motion estimation),
10. 計算攝影學 (computational photography),
11. 由運動求得結構與同步定位與地圖建構 (structure from motion and slam)
12. 深度估計 (depth estimation)
13. 三維重建 (3d reconstruction),
14. 以影像為基礎的繪圖 (image-based rendering),
介紹各種高等電腦視覺可能之應用,
並配合各項相關專題課程的需求研發適當之演算法及計算架構並完成軟體模擬。
將涵蓋:
1. 簡介 (introduction),
2. 影像形成 (image formation),
3. 影像處理 (image processing),
4. 模型擬合與最佳化 (model fitting and optimization),
5. 深度學習 (deep learning)
6. 辨認 (recognition)
7. 特徵偵測與配對 (feature detection and matching)
8. 影像對正與縫合 (image alignment and stitching)
9. 運動估計 (motion estimation),
10. 計算攝影學 (computational photography),
11. 由運動求得結構與同步定位與地圖建構 (structure from motion and slam)
12. 深度估計 (depth estimation)
13. 三維重建 (3d reconstruction),
14. 以影像為基礎的繪圖 (image-based rendering),
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 55人
射頻積體電路設計 - Rf Integrated Circuit Design
基因晶片方法與數據分析 - Genechips Methods and Data Analysis
基因遺傳演算法 - Genetic Algorithms
專利舉發與侵害鑑定實務 - Patent Opposition and Infringement
控制系統 - Control Systems
授課教師: 蔡坤諭
課程時間:112下-五789
上課地點: 電二101;
修課資訊: 【半年】【選修】【2,3,4 年級選修課程】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項: 本課程以英語授課。總人數限 30人
課程時間:112下-五789
上課地點: 電二101;
修課資訊: 【半年】【選修】【2,3,4 年級選修課程】【3學分】
課程概述:
[course description]
control is the action of causing a system variable to approach some desired value. it is also a fundamental and universal problem-solving approach in many traditional and interdisciplinary fields.
a control system, in a very general sense, is a system with an (reference) input that can be applied per the desired value and an output from which how well the system variable matches to the desired value (e.g., errors) can be determined. it can be found in daily life, almost all engineering disciplines, and even biological and social studies. for examples, bicycle riding involves a control system comprising of a bicycle and a rider, with inputs and outputs associated with the desired attitude, speed, and direction of the bicycle. temperature control systems have applications in household, automobile, aerospace, office, factory, and agriculture environments. motion control systems are critical to factory automation and precision instruments, such as industrial robots, atomic-force microscopes, and step-and-scan photolithography exposure systems. many modern cameras equip with autofocus and vibration compensation systems to minimize image blur. many kinds of circuits such as phase lock loops, operational amplifiers, and voltage regulators rely on control to ensure their functions and performance. a living body is a complex control system where many critical variables such as heartbeat rate, blood pressure, and body temperature are regulated constantly for health. central banks of most countries around the world set interest rates as a way to control inflation.
this undergraduate course is designed for junior and senior (3rd/4th yr.) students to apprehend basic modeling, simulation, analysis, and design techniques for control systems. it intends to cover the fundamentals of “classical control” that primarily focuses on frequency domain feedback control approaches for single-input-single-output systems. when time permits, some essential elements in modern-day control engineering such as state-space techniques will be covered.
control is the action of causing a system variable to approach some desired value. it is also a fundamental and universal problem-solving approach in many traditional and interdisciplinary fields.
a control system, in a very general sense, is a system with an (reference) input that can be applied per the desired value and an output from which how well the system variable matches to the desired value (e.g., errors) can be determined. it can be found in daily life, almost all engineering disciplines, and even biological and social studies. for examples, bicycle riding involves a control system comprising of a bicycle and a rider, with inputs and outputs associated with the desired attitude, speed, and direction of the bicycle. temperature control systems have applications in household, automobile, aerospace, office, factory, and agriculture environments. motion control systems are critical to factory automation and precision instruments, such as industrial robots, atomic-force microscopes, and step-and-scan photolithography exposure systems. many modern cameras equip with autofocus and vibration compensation systems to minimize image blur. many kinds of circuits such as phase lock loops, operational amplifiers, and voltage regulators rely on control to ensure their functions and performance. a living body is a complex control system where many critical variables such as heartbeat rate, blood pressure, and body temperature are regulated constantly for health. central banks of most countries around the world set interest rates as a way to control inflation.
this undergraduate course is designed for junior and senior (3rd/4th yr.) students to apprehend basic modeling, simulation, analysis, and design techniques for control systems. it intends to cover the fundamentals of “classical control” that primarily focuses on frequency domain feedback control approaches for single-input-single-output systems. when time permits, some essential elements in modern-day control engineering such as state-space techniques will be covered.
授課資訊: 課程說明 ; 臺大課程網
注意事項: 本課程以英語授課。總人數限 30人
通信原理 - Principle of Communications
授課教師: 蘇炫榮
課程時間:112下-四678
上課地點: 博理114;
修課資訊: 【半年】【選修】【2,3,4 年級選修課程】【3學分】
課程概述:
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 59人
課程時間:112下-四678
上課地點: 博理114;
修課資訊: 【半年】【選修】【2,3,4 年級選修課程】【3學分】
課程概述:
principle of communications is the first course to communication systems for undergraduate students, and it aims to uncover how a communication system works and the underlying beautiful theoretical principles. it builds the foundations for students to explore more advanced topics related to communications, ranging from theoretical development to practical implementation, such as wireless communications, wireless networks, internet of things, etc.. lectures are developed to answer the following key question: how to reliably deliver information over an unreliable physical medium?
towards answering this question, we begin with the interface between the cyber and the physical world and explain how to convert from digital to analog and vice versa. next, we introduce a first statistical model, the additive noise channel, that captures the unreliable feature of physical medium, and develop the principle for optimal reconstruction based on statistical decision theory. then, we introduce the key concept of coding in order to achieve reliable communication, together with some concrete examples of codes. these principles are extended to further channel models, namely, wireline (telephone) channel and wireless channel, where additional challenges such as inter-symbol interference (isi) and fading need to be tackled. ofdm is introduced to alleviate isi while diversity techniques are developed to mitigate fading.
towards answering this question, we begin with the interface between the cyber and the physical world and explain how to convert from digital to analog and vice versa. next, we introduce a first statistical model, the additive noise channel, that captures the unreliable feature of physical medium, and develop the principle for optimal reconstruction based on statistical decision theory. then, we introduce the key concept of coding in order to achieve reliable communication, together with some concrete examples of codes. these principles are extended to further channel models, namely, wireline (telephone) channel and wireless channel, where additional challenges such as inter-symbol interference (isi) and fading need to be tackled. ofdm is introduced to alleviate isi while diversity techniques are developed to mitigate fading.
授課資訊: 課程說明 ; 臺大課程網
注意事項: 總人數限 59人