本課程為研究所課程，課程內容包含適應性系統之介紹與其控制設計應用。針對具有未知參數之系統，鑑別未知參數之行為並分析與設計相關之控制器。運用線性系統及非線性系統理論，介紹智慧型控制與適應控制的技巧，對各種不同的未知系統設計出理想的控制器並達到強韌控制的效果。除適應控制設計之外，並將介紹一些智慧型性控制之設計方法，其中包含類神經網路控制與順滑模式控制設計，並結合適應控制之理論，運用至各種系統上。藉由本課程之理論，同學們將可處理大部分具有未知參數及不確定性之系統，並認識其相關之控制應用。 課程主要內容如下:

introduction
identification of system parameters
adaptive control of linear systems
adaptive control of a class of nonlinear systems
adaptive neural network control
adaptive sliding mode control

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: 簡介 (introduction), 影像形成 (image formation), 影像處理 (image processing), 特徵偵測與配對 (feature detection and matching), 影像分割 (segmentation), 以特徵為基礎的定位 (feature-based alignment), 由運動推出結構 (structure from motion), 細密運動估計 (dense motion estimation), 影像縫合 (image stitching), 計算攝影學 (computational photography), 立體對應 (stereo correspondence), 三維重建 (3d reconstruction), 以影像為基礎的繪圖 (image-based rendering), 辨識 (recognition)。

本課程分為幾個部分：
(1) 數位濾波器設器 (含 iir, fir, wiener，信號還原技術)
(2) 同質訊號系統(含倒頻譜，梅爾倒頻譜)
(3) 聲音信號處理
(4) 壓縮的技術 (含壓縮的通則，編碼技巧)
(5) 快速演算法的設計 (含快速演算法的通則，質因數的快速傅立葉轉換)
(6) 正交轉換 (含瓦爾西轉換，數論轉換，cdma)
(7) 其他 (如結構相似度，頻譜分析的正確方法，影像和信號處理常識)

自人類基因體解碼後，各種人體基因和蛋白體數據的產生，已經無法由傳統生物學的研究模式解析生命的複雜，以及疾病發生的原因。取而代之的是一個分析巨量資料時代的來臨。各種檢驗的影像和體學的醫療數據，都需要仰賴生醫資訊和人工智慧進行探勘和建立預測模型，以期能給病人更佳的診斷和治療。此課程主要著重在探究最新的計算與系統生物學的工具和研究課題。

the study of algorithms is at the heart of computer science. this course focuses on fundamental results in this area, including the unifying principles and underlying concepts of algorithm design and analysis.
we expect everyone to be comfortable reading, even writing, proofs. several programming assignments will be given to embody the ideas. moreover, we hope that everyone can learn general problem-solving techniques.

.admission from the lecturer is required.

this course will cover fundamental knowledge on microelectromechanical systems (mems) technology applied on biological application. students will choose a lab-on-chip device and analyze its performance as the final project. the course will include three main parts:
1. biomems fabrication and materials
2. biomems and microfluidics design
3. microfluidics and lab-on-chip applications.

以熱力學、固體及流體力學、電生理學為主要觀點，講解細胞如何控制整體及個別分子行為，以如何傳遞及能量和訊息。課程內容著重於細胞的物理模型

這是一門半學期的課程，主要介紹多變數函數的微積分運算，和其豐富的應用。微分主題包含多變數函數的極限，偏微分，方向導數，切平面，線性逼近，和微分連鎖律；並討論求函數極值，lagrange乘子法等應用問題。積分部分涵蓋多重積分與逐次積分的定義，fubini定理，和變數變換；並以求實體質量、質心等幾何量作為其應用。課堂上將講解定義並推導重要定理，以培養學生邏輯推理與分析能力；同時會示範微積分在各領域的應用，幫助學生將微積分與其他專業科目結合。本課程還設有習題課，學生將在助教的帶領下熟練微積分的計算。

calculus of multivariable functions together with its profound applications are introduced in this half-semester course. specifically, topics about differentiation include limits, partial derivatives, directional derivatives, tangent planes, linear approximations, and the chain rule. also, applications such as finding extreme values and methods of lagrange multipliers are discussed. topics about integration involve definitions of multiple integrals and iterated integrals, fubini’s theorem, change of variables, as well as applications such as computing the mass and center of mass of a solid. definitions are discussed and the most important theorems are derived in the lectures with a view to help students to develop their abilities in logical deduction and analysis. practical applications of calculus in various fields are illustrated in order to promote a more organic interaction between the theory of calculus and students own fields of study. this course also provides discussion sessions in which students are able to make their skills in handling calculations in calculus more proficient under the guidance of our teaching assistants.

本課程中文授課,使用英文教科書。密集課程。密集課程，統一教學，一10為實習課，期考於周末舉辦。總人數限 90人限本系所學生(含輔系、雙修生)

這是一門半學期的課程，主要介紹多變數函數的微積分運算和其豐富的應用。

微分主題包含多變數函數的極限、偏微分、方向導數、切平面、線性逼近和微分連鎖律，並討論求函數極值、lagrange乘子法等應用問題。積分部分涵蓋多重積分與逐次積分的定義、fubini定理和變數變換，並以求實體質量、質心等幾何量作為其應用。

課堂上將講解定義並推導重要定理，以培養學生邏輯推理與分析能力；同時會示範微積分在各領域的應用，幫助學生將微積分與其他專業科目結合。本課程還設有習題課，學生將在助教的帶領下熟練微積分的計算。

本課程中文授課,使用英文教科書。密集課程。密集課程，統一教學，一10為實習課，期考於周末舉辦。總人數限 90人限本系所學生(含輔系、雙修生)

這是一門半學期的課程，分為「向量微積分」與「泰勒展式」兩大主題。
「向量微積分」討論的主體是定義域、值域皆屬於 r^n的函數(又稱為「向量場」)。我們將定義如何在曲線或曲面上積分向量場，並介紹作用在向量場上的兩種微分運算，「散度」與「旋度」。課程將解釋green定理、stokes定理、散度定理如何結合向量場的微分與積分運算，而被理解為高維度的「微積分基本定理」。應用上，我們將推導電磁學中的 gauss 定律，計算封閉曲面的電通量。
「泰勒展式」這主題推廣「極限」的概念，探討如何以多項式逼近複雜的函數。為了達到這個目的，我們將介紹無窮級數與冪級數的收斂性，利用泰勒定理估計餘項，進而推導出常見函數的泰勒展式。最後我們將示範多項式逼近的實際應用。
課堂上將講解定義並推導重要定理，以培養學生邏輯推理與分析能力；同時會示範微積分在各領域的應用，幫助學生將微積分與其他專業科目結合。本課程還設有習題課，學生將在助教的帶領下熟練微積分的計算。

this half-semester course contains two main topics which are vector calculus and taylor series.
vector calculus deals with functions whose domain and range are both in r^n which are also called vector fields. we will make sense of integrating vector fields over curves and surfaces and introduce two differential operators acting on them, the divergence and curl. we will explain how green’s theorem, stokes’ theorem, and the divergence theorem connect the integration and differentiation of vector fields and are regarded as higher-dimensional fundamental theorem of calculus. as an application, we will derive gauss law in electromagnetism that describes the flux of an inverse square field across a closed surface.
the topic of taylor series extends the concept of limit to approximating complicated functions by polynomials. we will introduce the convergence of series and power series, use taylor’s theorem to estimate remainder terms, and derive taylor series for common functions. finally, applications of approximating functions by polynomials are illustrated.
definitions are discussed and the most important theorems are derived in the lectures with a view to help students to develop their abilities in logical deduction and analysis. practical applications of calculus in various fields are illustrated in order to promote a more organic interaction between the theory of calculus and students own fields of study. this course also provides discussion sections in which students are able to make their skills in handling calculations in calculus more proficient under the guidance of our teaching assistants.

本課程中文授課,使用英文教科書。密集課程。密集課程，統一教學，一10為實習課，期考於周末舉辦。總人數限 90人限本系所學生(含輔系、雙修生)

本課程中文授課,使用英文教科書。密集課程。密集課程，統一教學，一10為實習課，期考於周末舉辦。總人數限 90人限本系所學生(含輔系、雙修生)

本課程介紹以gaas及inp為主的三五族化合物半導體材料系統的磊晶及製程技術。
一、 光電半導體材料的種類及基本特性
二、 塊材成長技術
三、 真空技術
四、 磊晶技術：分子束磊晶法
五、 磊晶技術：有機金屬化學沈積法
六、磊晶技術：液相磊晶法

introduction1. introduction to soc vlsi interconnect design and analysis2. soc design challenges and potential solutions3. power and signal integrity analysis and optimizationinterconnect modeling and simulation 4. formulation of circuit equation 5. solution of linear equations 6. interconnect delay models 7. laplace transformation and analysis 8. transient simulation9. model order reduction 10. interconnect modeling i: capacitance extraction11. interconnect modeling ii: inductance extraction12. iterative solution of linear equations & applicationnonlinear circuit simulation13. solution of non-linear equations 14. transient analysis of nonlinear dynamic circuits 15. consistency, stability, convergence , local truncation error circuit optimization16. mathematical programming i: linear programming 17. mathematical programming ii: nonlinear programming 18. mathematical programming iii: geometric programming19. combinatorial optimization i: greedy algorithm20. combinatorial optimization ii: dynamic programming

topics covered in this course are as follows:

1. computer abstractions and technology
2. instructions
3. arithmetics
4. processors
5. memory hierarchy

1. the basic concept of risc (reduced instruction set computer), compared with cisc (complex instruction set computer)
2. the assembly/machine language of the mips cpu
3. detailed cpu design:
instruction set, data path, control unit, arithmetic logic unit (alu),
techniques to enhance cpu performance, e.g., pipelining and hazard control
4. memory hierarchy:
cache (l1$, l2$, etc.): how to improve data/instruction access time for cpu?
virtual memory: how to handle program/data that is larger than your physical (main) memory?
5. i/o peripherals:
know more about i/o devices and networking devices
6. new trend of multi-core cpus (overview)

1.introduction
2.the application layer
3.the transport layer
4.the network layer
5.the data link layer
6.the physical layer

1.basic simulation modeling
2 modeling complex systems
3 review of basic probability and statistics
4 building valid, credible, and appropriately detailed simulation models
5 selecting input probability distributions
6 random-number generators
7 generating random variates
8 output data analysis for a single system
9 comparing alternative system configurations
10 variance-reduction techniques
11 case studies in manufacturing systems & telecommunication networks

本課程的內容涵蓋電腦視覺的多個面向，從image processing, recognition/detection, 到geometry等方向都在課程內容之中，期能讓修課同學對電腦視覺領域有完整的認識。
課程網要如下：
introduction to human vision systems
camera basic, image formation and basic image processing
feature detection and matching
machine learning basics
deep learning basics
recognition and detection
segmentation
projective geometry, transformations and estimation/camera calibration
camera geometry and single view geometry
two-view geometry
dense motion estimation/stereo
structure from motion
3d reconstruction/depth sensing
computational photography
object tracking
advanced topics in cv
.

課程網站 ： http://media.ee.ntu.edu.tw/courses/cv/21s/