902 10730 - 物件導向程式設計

Java language:
1. object
2. method
3. array
4. inheritance
5. polymorphism
6. virtual
7. interface
8. encapsulation
9. exception
10. thread
11. event

902 10740 - 資訊系統原理

This is an introduction course to make students familiar with the modeling techniques for the design and implementation of the information system. A successful software organization is one that consistently deploys the quality information system that meets the needs of its users. A complete modeling technique can develop such software in a timely and predictable fashion, with an efficient and effective use of resources, both human and material. Modeling is a central part of all the activities that lead up to the deployment of good software. We build models to communicate the desired structure and behavior of our systems. We build models to visualize and control the system’s architecture. We build models to better understand the system we are building, often exposing opportunities for simplification and reuse. We build models to manage risk.

In the class, I will share the following major topics with students.

• Introduction to the Unified Modeling Language
• Basic Structural Modeling
• Advanced Structural Modeling
• Basic Behavioral Modeling
• Advanced Behavioral Modeling
• Architectural Modeling

902 21400 - 數位電子學

• Introduction to Digital Electronics
• Solid-State Electronics
• Solid-State Diodes and Diode Circuits
• Field Effect Transistors
• Introduction to Digital Electronics
• MOS Logic Design
• CMOS Logic Design
• MOS Memory and Advanced Logic Circuits

902 21400 - 數位電子學

• Introduction to Digital Electronics
• Solid-State Electronics
• Solid-State Diodes and Diode Circuits
• Field Effect Transistors
• Introduction to Digital Electronics
• MOS Logic Design
• CMOS Logic Design
• MOS Memory and Advanced Logic Circuits

902 44000 - 系統程式

1. Introduction – Chapter 1
2. Unix Standardization and Implementation – Chapter 2
3. File I/O – Chapter 3
4. Standard I/O Library – Chapter 5
5. Files and Directories – Chapter 4
6. System Data Files and Information – Chapter 6
7. The Environment of a Unix Process – Chapter 7
8. Process Control – Chapter 8
9. Signals – Chapter 10
10. Interprocess Communication – Chapter 14 (partially)

902 44000 - 系統程式

System programming is one of the core knowledge for computer engineers/researchers. The goal of this course is to strengthen students’ knowledge on operating systems and students’ skills on programming on the system level. The topics of this class include

• Unix Standardization and Implementation
• File I/O
• Standard I/O Library
• Files and Directories
• System Data Files and Information
• The Environment of a Unix Process
• Process Control
• Signals
• Interprocess Communication

902 25702 - 資料結構與演算法下

1.Hash Tables
2.Dynamic Programming
3.Greedy Algorithms
4.Amortized Analysis
5.Fibonacci Heaps
6.Graph Algorithms
7.Matrix Operations
8.Number-Theoretic Algorithms
9.String Matching

902 39200 - 編譯程式設計

Introduction
Scanner
Grammar
Parsing
Top-down Parsing
Bottom-up Parsing
Symbol Table
Semantic Processing
Declaration
Expression
Statement
Optimization
Code Generation

902 39200 - 編譯程式設計

Introduction

Lexical analysis (Scanner):

regular expressions, finite state machine, LEX

Syntax analysis (Parser):

recursive descent parsing, LL(1), operator precedence parsing, SLR, LR(1), LALR, YACC

Syntax-directed translation

Symbol tables, type checking

Run time environments

Intermediate code generation

Semantic processing (code generation):

declarations, expressions, advanced data structure, control flow, procedure/function

Building a compiler

Advanced topics (if time allowed):

error handling, optimization, ...

902 46100 - 計算機結構

1. Fundamentals of Computer Architecture: (chapter 1)
cost and performance measurement
2. Instruction Set Design and Basic Pipelining: (chapter 2 and 3)
DLX architecture
3. Exploiting Instruction Level Pipelining: (chapter 4)
multiple issue processor and compiler support
4. Memory Hierarchy Design: (chapter 5)
cache and virtual memory
5. I/O System Design (chapter 6)
6. Multiprocessors: (chapter 8)
parallel architecture and memory consistence models.

902 39120 - 計算機網路實驗

The object of the course is to make students familiar with computer networks, especially the wireless networks. The students will design and implement various technologies for the firewall and Mobile IP topics. The following topics will be covered in this course:

(1) Setup a hacker-proof but useful firewall.
(2) Implement the authentication mechanism for the 802.11 network.
(3) Implement the Mobile IP and multicast mechanism on the IPv4 network.
(4) Simulate wireless networks by using “Network Simulator - ns-2” simulation tool.

902 34100

This course will cover the fundamental concepts and various aspects of programming languages including syntax, semantics, and implementations. The topics that will be discussed include:

1. Representation of syntax rules.
2. Interpretation of semantics and their implications.
3. Varible scopes and binding rules.
4. Data types and type checking.
5. Expression and assignment statements.
6. Control flow statements.
7. Concept of structural programming and subroutines.
8. Object-oriented programming concept and methodology.
9. Comparison of various programming models, including imperative, logic, and functional programming.

921 U1120

This is a first course on computer processing of speech signals. Both theoretical issues and practical problems will be discussed, and both fundamental concepts and research topics will be emphasized. The viewpoints will be centralized on the vision of user-network voice interaction for future wireless world.

Part I: Fundamental Topics
1. Digital Speech Processing
2. Fundamentals of Speech Recognition
3. Map of Subject Areas
4. More about Hidden Markov Models
5. Acoustic Modeling
6. Language Modeling
7. Speech Signals and Front-end Processing
8. Search Algorithms for Speech Recognition
Part II: Research Topics
9. Some Fundamental Problem-solving Approaches
10. Utterance Verification and Keyword/Key Phrase Spotting
11. Speaker Variabilities: Adaption and Recognition
12. Latent Semantic Analysis for Linguistic Processing
13. Speech-based Information Retrieval
14. Robustness for Acoustic Environment
15. Spoken Dialogues
16. Distributed Speech Recognition and Wireless Environment

922 M0110 - 軟體系統

Topic: Instant message systems & applications
1. Peer-to-peer (P2P) infrastructure
2. Hybrid P2P architecture
3. Primary application -- mail & message
4. Workflow platform -- message based
5. Heterogeneous groupware -- form based
6. Gateway server for mobility support
7. Integration with application server
8. Metrics issue9. Security issue

922 M0740

1. Multicast issues on ad hoc wireless networks
2. Broadcast problem on ad hoc networks
3. MAC protocols for UWB wireless networks
4. QoS-aware services on WLAN
5. Study of IPv6 in 3G

922 U0100 - 腦理論

The syllabus collected span the history of the field since its inception. Brain theory is the endeavor to understand mind (thinking, intellect) in terms of its design (how it is build, how it works).

• Computational mental process, Longuet-Higgins, H.C.
• Winograd's SHRDLU program
• Mental process, formal system, language
• Neurobiological modeling
• Perception and associative memory

922 U0110

Website: http://homepage.iis.sinica.edu.tw/~dtlee/CSIE/

922 U0140

Machine learning, data mining, and knowledge discovery are growing rapidly in importance and commercial interest as more data becomes available online.

In this course we will focus on machine learning techniques for data mining. That is, assuming data have been preprocessed, we apply machine learning techniques for extracting useful knowledge. In particular, we will discuss clustering and classification methods in detail.

If time is allowed, we will touch modeling issues of data mining problems.

922 U0160 - 無線多媒體系統研究

• Introduction to Wireless Networks
• Propagation Channel Model
• Channel Coding
• The Cellular Concept
• Multiple Radio Access
• Multiple Division Techniques
• Channel Allocation
• Mobile Communication System
• Existing Wireless System
• Satellite System
• Network Protocol
• Ad Hoc and Sensor Networks
• Wireless LANs and PANs

922 U0190

本專題課程首先將平行計算作一概括式介紹。介紹方法將是以叢集計算作為理論及實驗平台。介紹內容將包括平行計算模型（parallel computation model），包括了PRAM（parallel random access machine model），分散式及共享記憶體計算模式（distributed/shared memory models），特殊連結網路計算模式（special interconnection network model）。另外本課程也將介紹在各個計算模型下適用的程式撰寫模式，包括了共享記憶體程式撰寫模式（shared memory programming model），單一指令複合資料模式（SIMD，single instruction multiple data），複合指令複合資料模式（MIMD，multiple instruction multiple data），及單一程式複合資料模式（SPMD，single program multiple data）。

本專題課程再進一步會介紹平行計算所使用的各種演算法（parallel algorithms），以及他們與一般循序演算法（sequential algorithms）的差別。各種效能評估指標包括速度增益（speedup）及平行效率（parallel efficiency）也將在本課程中提出討論。本課程同時會在本課程組所提議之個人電腦叢集實作部分在課堂上所討論的平行演算法，用已驗證演算法所提出的理論部分。在實作方面將會使用平行計算程式庫包括Pthread（POSIX thread library），MPI（Message passing interface），及PVM（Parallel virtual machine）。修習本課程學生將會在此一提議之個人電腦叢集獲得充分平行程式撰寫經驗，來和理論比較驗證。

本專題課程進一步將著重在平行處理中通訊最佳化的問題討論，尤其是在個人電腦叢集中如何處理集體通訊（collective communication）的課題。在平行計算中處理節點（processing node）之間的通訊往往對平行處理的效率有極大的影響。隨著微處理機的發展日新月異，計算時間相形之下可大幅縮短，但是處理節點之間的通訊往往造成效能提升上的瓶頸。如何在個人電腦叢集中頻寬有限的情況下仍能有效的提升通訊效能就成為一個重要課題。

平行處理中往往需要使用集體通訊在處理節點之間傳遞資訊。這些集體通訊包括了點對所有點單一資訊廣播（broadcast），點對多點單一資訊廣播（multicast）, 所有點對所有點客制資訊傳播（all to all personalized communication），以及所有點對單點資訊歸納（reduction）。這些通訊模式（communication pattern）都有其特殊性而且在平行處理中被普遍使用，所以這些通訊模式在實作上的效能對平行處理的整體效能有極大影響。

因應個人電腦叢集中可能會有不同種類的處理節點，傳統應用於同質性叢集系統（homogeneous cluster system）的通訊模式最佳化演算法必須加以調整。新的通訊模式最佳化演算法必須針對異質性叢集系統（heterogeneous cluster system）中不同種類的處理節點會有不同的計算速度及通訊頻寬而設計。這對通訊最佳化演算法設計帶來了新的挑戰與研究課題。本課程也將對此一問題作深度探討。

922 U0270 - 財務演算法

• Time value of money
• Bonds, mortgages, and annuities
• Duration, convexity, and immunization
• Yield curve, forward rate, and spot rate
• Option pricing theory and its wide-ranging applications
• Black-Scholes analysis
• binomial option pricing model (BOPM)
• Futures, forwards, and other derivatives
• The combinatorics of random walks
• Martingale, Brownian motion, stochastic calculus, and Ito integral
• Risk-neutral valuation
• Risk management
• Fixed-income securities with embedded options and interest rate derivatives
• Mortgage-backed securities (MBS)
• Numerical methods
• Monte Carlo methods
• Variance reduction (efficiency-improving) techniques
• Quasi-Monte Carlo method
• Solving partial differential equations
• Yield curve fitting
• Interest rate models and calibration

922 U0310 - 網際網路電話系統

This course will introduce the followings:

(1) Introduction
(2) Transporting Voice using IP: RTP
(3) Speech-coding Techniques
(4) H.323
(5) SIP
(6) MGCP/MEGACO
(7) VoIP and SS7
(8) ENUM
(9) Number Portability
(10)3GPP All IP Network

922 U0350

1. Introduction
2. Data warehousing and OLAP technology for data mining
3. Concept description: Characterization and comparison
4. Mining association rules in large databases
5. Classification and prediction
6. Clustering analysis
7. Web Content Mining
8. Web Structure mining
9. Web Usage mining
10. Data mining applications and trends in data mining

922 U0360 - 軟體專利實務之基礎

1. What a patent is, as a contract with government, as intellectual property; and what some common misconceptions about patents are, about its conception, its magic, its validity.
2. The computer software invention and its relation with software patents; invention and engineering; discovery and invention; non-statutory subject matter.
3. The statutory subject matter --- as processes: computer programs and product-by-process; as products: machine (apparatus), manufacture, and composition of matter.
4. Novelty --- prior art, anticipation, doctrine of inheritance, and use in public, experiment, or secret.
5. Utility --- useful and operability.
6. Non-obviousness --- negative rules of invention, non-obviousness standard, analogousness, equivalence, simplicity, predictability, superiority, optimization, and identifying the source of a problem and its solution.
7. The computer program-related inventions --- framework of laws, patent protection, multinational bodies, and policy.
8. Preparation of patent applications --- the patent specification: title and abstract, cross-references to other applications, background of the invention, summary of the invention, brief description of the drawings, detailed description of the best mode; duty of disclosure.
9. Patent claims --- analysis and synthesis: purpose of the patent claims, novel structure, implicit three unities, claim syntax, and claim grammar.
10. Prosecuting patent applications --- filing, ex parte prosecution, restriction, rejections, correction, and re-examination.

922 U0380

Course Introduction

This course covers the design and architecture of FEC (forward error correction) system. We will approach the FEC design from both system perspective and implementation perspective. This course starts with an overview of FEC systems and introduction to information theory, followed by discussions of the classical FEC components (Viterbi decoders, TCM decoder, Reed-Solomon decoder, …). Real FEC systems will be used as examples to discuss design choices and architecture trade-offs. In addition, we will also look at some next-generation error correction codes like LDPC codes.

Course Outline

1. Overview of FEC System
2. Introduction to Information Theory
3. Convolutional Codes and Viterbi Decoder
4. Trellis Coded Modulation
5. Block Codes and Reed-Solomon Decoder
6. FEC System Implementation Examples (DBS, COFDM, DSNG)
7. LDPC codes and Iterative Decoder

922 U1030 - 資訊理論與編碼技巧

資訊理論與編碼技巧係數位通訊領域核心課程之一，由資訊之測量至資料的有效表現均為本課程包含之範圍。本課程之內容 將包含以下之主題：

1.資訊理論基礎

• Entropy Function
• Source Coding Theory

2.無失真壓縮技術

• Huffman Coding
• Arithmetic Coding
• LZ-Coding
• Predictive Coding

3.有失真壓縮技術

• Quantization
• Transform-coding
• Vector-Quantization
• Subband coding
• Multi-resolution
• Perceptual coding

4.多媒體資料壓縮技術

• Audio data Compression
• Image data Compression
• Video data Compression (Motion Estimation)

5.壓縮標準簡介

• JPEG
• MPEG-1
• MPEG-2
• H.26X

922 U1200 - 電腦視覺二

講授電腦視覺之基本觀念及立論基礎。 介紹各種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:

照明 (Illumination)
透視投射幾何學 (Perspective Projective Geometry)
分析式照相測量術 (Analytic Photogrammetry)
序列照片中找出運動與表面結構 (Motion and Surface Structure from Time Varying Image Sequences)
影像比對 (Image Matching)
物件模型與比對 (Object Models and Matching)
知識為基礎的視覺 (Knowledge-Based Vision)
準確度 (Accuracy)

922 U1320

Major Topics
1. The OSI Model
2. LAN and Bridges
3. WAN and Routers
4. TCP/IP
5. IP Addressing
6. Routing Protocols
7. LAN Switching
8. VLAN
9. Access Control Lists
10. WAN Design
11. PPP
12. Frame Relay

922 U1330 - 高等計算機網路

Website: http://www.csie.ntu.edu.tw/~ccf/spring2004/syllabus.htm

922 U1580

“The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” … Mark Weiser, “Computer for the 21th Century”, Scientific American, September, 1991.

Pervasive & ubiquitous computing is how computing will be used in the future. It is about moving beyond the traditional desktop computing model, into embedding and applying computing into everyday objects and everyday activities. The vision is that the virtual computing space will be so seamlessly integrated with our physical environment, such that we as people cease to take notice of computing. In this course, we will study the following topics to realize this vision of ubiquitous computing: (1) software infrastructure for pervasive computing that can support the integration between our physical space and virtual computing space, (2) sensors and sensor network that can capture and disseminate context information, (3) context-aware applications that use context information to create intelligent everyday objects and applications, (4) embedding computing into everyday objects, (5) user interfaces for ubiquitous computing, (6) security and privacy to protect access to user context information, (7) migration where an application context can migrate from one computing environment to another computing environment, (8) spontaneous interaction where appliances and services can seamlessly interact and interoperate with each other with little or no prior agreements, and (9) social computing that apply ubiquitous computing techniques and everyday computing artifacts to improve our social lives.

This is a graduate-level course with the goal to prepare undergraduate seniors and graduate students for research in the ubiquitous computing. This course will have two main components: paper readings and hands-on projects. The papers will be drawn from IEEE Pervasive Computing Magazines, as well as supplements from conference proceedings. In the hands-on projects, students will form teams to explore actual design and prototype of ubiquitous computing systems or applications.

This course will be taught in English.

COURSE PRE-REQUISITE

Students should have some background in operating systems, distributed systems, computer networks, and mobile computing. Students are expected to have (or learn on their own) necessary programming skill to prototype their projects.

922 U1690

This course is intended to provide a comprehensive technical survey of the important topics in production automation and related topics. These topics include Production system Planning and Scheduling, Computer Integrated Manufacturing, Flexible Manufacturing System, Group Technology, and etc. Thos course requires no prerequisite and is suitable for engineering students at the advanced undergraduate (junior and senior) and beginning graduate level.

Topics to Be Covered

1.Fundamentals of Production and Automation
2.Material Handling and Storage
3.Industrial Robotics
4.Group technology and Flexible Manufacturing System
5.Computer Integrated Manufacturing
6.Production System Modeling: Petri-Net Approach
7.Production system Scheduling: Artificial Intelligence Approach

922 U1910 - 資訊檢索與擷取

1. Introduction to Information Retrieval and Extraction
2. Modeling
3. Retrieval Evaluation
4. Query Languages
5. Query Operations
6. Text and Multimedia Languages and Properties
7. Text Operations
8. Indexing and Searching
9. User Interfaces and Visualization
10. Multimedia IR: Models and Languages
11. Multimedia IR: Indexing and Searching
12. Searching the Web
13. Digital Libraries
14. Chinese Information Retrieval
15. Cross-Language Information Retrieval
16. Information Extraction (Jerry R. Hobbs)
17. Text Data Mining (Marti Hearst)

922 U1920

一、傳統之密碼學，如DES，IDEA。
二、非對稱式密碼學，如RSA，EL Gamal。
三、資訊戰爭攻防戰術。
四、國家密碼政策。
五、各種密碼協定。
六、公鑰基礎建設理論。

922 U1940 - 虛擬實境

PartⅠ: Virtual Reality

Look real, sound real, feel real, smell real, react realistically and in real-time

3D Sound, directional sound

Environment Walkthrough, Distributed Interactive Simulation (DIS)

Tracking devices: space tracker, tracking algorithms

Immersive display: Head Mounted Display, BOOM, Stereo shutter glasses

Force Feedback Devices (Joystick, Phanton etc.)

Trajectory prediction algorithms

Part Ⅱ: Display and Visualization

Modeling (Solid modeling, build large models, physically based modeling: motion dynamics)

Global illumination algorithms( radiosity, volume rendering, scientific visualization)

Texture mapping and advanced animation

Graphics packages : OpenGL (X window, WinXP), DirectX(WinXP)

Part III: Hardware and accelerators

High performance graphics architectures

(Pixel-Planes, Pixel Machine, SGI reality engine, PC Graphics (nVidia, ATI), Accelerator Chips & Cards)

Part IV:

Virtual reality paper survey and term project

922 U3020 - 人工智慧

1. Introduction and overview --What is AI?
2. Search techniques: Uninformed search, Heuristic search, Adversary search
3. Knowledge representation: Logic, Frames, Semantic nets, Common sense knowledge
4. Reasoning techniques: Forward/Backward chaining resolution
5. AI programming languages
6. Planning
7. Learning

922 U3030 - 圖形分析辨認

The goal of this course is to introduce the basic concepts and techniques used in the field of pattern recognition (PR). Broadly speaking, PR is a science that concerns the classification (or recognition) of measurements. It has many important applications, for example, document analysis, face recognition, fingerprint identification, speech recognition, medical diagnosis, data mining, and information retrieval. The outline of this course is given below.

I. Pattern Recognition Overview
II. Bayesian Decision Theory
III. Supervised Learning Using Parametric Approaches
IV. PCA and LDA
V. Supervised Learning Using Non-parametric Approaches
VI. Linear Discriminant Functions
VII. Unsupervised Learning and Clustering
VIII. Other Related Topics

922 U3050 - 分散式代理人系統

This course introduces the theory, construction, and application of multiagent systems.

• Agent-oriented software engineering
• Multiagent interaction technology
1. Agent communication
2. Collaboration, competition, and negotiation
• Distributed computing infrastructure
1. P2P networking
2. Semantic Web services
3. Agent-related standard protocol
• Distributed artificial intelligence
• Multiagent system applications
1. Electronic marketplace
2. Supply-chain management
3. Real-time management and control
4. Social computing

922 U3060 - 圖形演算法特論

In this course, we will focus on algorithms for spanning trees. Some related topics will also be covered.

Prerequisites: Some basic knowledge on algorithm development is required. Background in approximation algorithms is welcome but not required for taking this course.

Outlines:

1. Counting spanning trees
2. Minimum spanning trees
3. Shortest-paths tree
4. Minimum routing cost spanning trees
5. Communication spanning trees
6. Optimal product-requirement communication spanning trees
7. Optimal sum-requirement communication spanning trees
8. Light approximate shortest-paths trees
9. Light approximate routing cost spanning trees
10. Steiner minimal trees
11. Trees and diameters
12. Other advanced topics

922 U3070 - 普及計算

`The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.`, Mark Weiser, “Computer for the 21th Century”, Scientific American, September, 1991.

Pervasive & ubiquitous computing is how computing will be used in the future. It is about moving beyond the traditional desktop computing model, into embedding and applying computing into everyday objects and everyday activities. The vision is that the virtual computing space will be so seamlessly integrated with our physical environment, such that we as people cease to take notice of computing. In this course, we will study the following topics to realize this vision of ubiquitous computing: (1) software infrastructure for pervasive computing that can support the integration between our physical space and virtual computing space, (2) sensors and sensor network that can capture and disseminate context information, (3) context-aware applications that use context information to create intelligent everyday objects and applications, (4) embedding computing into everyday objects, (5) user interfaces for ubiquitous computing, (6) security and privacy to protect access to user context information, (7) migration where an application context can migrate from one computing environment to another computing environment, (8) spontaneous interaction where appliances and services can seamlessly interact and interoperate with each other with little or no prior agreements, and (9) social computing that apply ubiquitous computing techniques and everyday computing artifacts to improve our social lives.

This is a graduate-level course with the goal to prepare undergraduate seniors and graduate students for research in the ubiquitous computing. This course will have two main components: paper readings and hands-on projects. The papers will be drawn from IEEE Pervasive Computing Magazines, as well as supplements from conference proceedings. In the hands-on projects, students will form teams to explore actual design and prototype of ubiquitous computing systems or applications.

This course will be taught in English

For additional information on this course, please visit the following URL: http://www.csie.ntu.edu.tw/~hchu/ubicomp_course/ubicomp_course.htm

922 U3120 - 醫療資訊系統

1. 醫療資訊標準 HL 7
2. 門診住院資訊系統
3. 急診資訊系統
4. 檢驗資訊系統 LIS
5. 數位影像系統 PACS
6. 電腦化醫療儀器
7. 遠距醫療
8. 電子病歷
9. 醫療資訊安全

922 U3130

1. secret key encryption
2. public key encryption
3. hashing
4. digital signatures
5. real world cryptography
6. authentication
7. email security
8. ip security
9. web security

922 U3140

Part 1: Encryption Schemes
(a) The Basic Setting and Definitions of Security
(b) Constructions of Secure Encryption Schemes
(c) Advanced material
Part 2: Digital Signature and Message Authentication
(a) Definitional Issues
(b) Length-restricted signature scheme
(c) Basic Constructions
(d) Advanced material
Part 3: General Cryptographic Protocols
(a) A detailed overview
(b) The two-party case
(c) The multi-party case

922 U3150 - 數位視覺效果

Website: http://www.csie.ntu.edu.tw/~cyy/courses/vfx/04spring/overview/

922 U3160 - 連網型嵌入式系統

The purpose of this course is to get the students familiar with the knowledge and hands-on programming skills for networked SoC systems. The lectures will cover the topics including real-time operating systems, real-time embedded programming, power management, networks for embedded system, mobile ad hoc networks and real-time networking. The labs will guide the students to practice the programming skills for networked embedded systems.

At the end of the semester, the students will build an intelligent transportation coordination system on robot cars. The cars will be equipped with IR sensors or camera to guide the car to follow the walls or lines, a wireless communication module to communicate with the traffic controller or other robot cars on the street, and a single board computer with Intel Xscale processor. With the intelligent transportation coordination system, the car should stop at the intersection when a control command is received from the traffic controller via the wireless network and should communicate with other cars on the street to avoid the collision. Otherwise, the car should move as fast as possible toward its destination. The car should also try to prolong the life time of the on-board computer via dynamically adjusting the power level of the processor.

This course consists of two hours lecture and two hours labs per week. The teaching materials, lab materials, and handout will be distributed in class or in electronic form.

922 U3160 - 連網型嵌入式系統

The purpose of this course is to get the students familiar with the knowledge and hands-on programming skills for networked SoC systems. The lectures will cover the topics including real-time operating systems, real-time embedded programming, power management, networks for embedded system, mobile ad hoc networks and real-time networking. The labs will guide the students to practice the programming skills for networked embedded systems.

At the end of the semester, the students will build an intelligent transportation coordination system on robot cars. The cars will be equipped with IR sensors or camera to guide the car to follow the walls or lines, a wireless communication module to communicate with the traffic controller or other robot cars on the street, and a single board computer with Intel Xscale processor. With the intelligent transportation coordination system, the car should stop at the intersection when a control command is received from the traffic controller via the wireless network and should communicate with other cars on the street to avoid the collision. Otherwise, the car should move as fast as possible toward its destination. The car should also try to prolong the life time of the on-board computer via dynamically adjusting the power level of the processor.

This course consists of two hours lecture and two hours labs per week. The teaching materials, lab materials, and handout will be distributed in class or in electronic form.

922 U3170 - 數學模擬與系統生物

This will be a special topics course that focusing on recent work that involves modeling metabolic, signaling, and gene regulation networks in cells, with a particular focus on using machine learning methods to analysis, synthesis, design and control the models from data. Qualitative and quantitative mathematical models that accurately predict physical phenomena are essential in many fields of engineering and science. This course will cover following topics:

1. Graphical representation of biochemical systems;
2. Models of biochemical systems;
3. From maps to equations;
4. Computer simulation;
5. Parameter estimation;
6. Analytical steady-state evaluation;
7. Sensitivity analysis;
8. Case study: S-System

922 U3180

This course will cover the technology trend and industry trend in the fields of multimedia and networking technologies. This course will invite industry leaders as well as scholars to share their experiences and visions in this field.

922 U3200

1. Introduction
2. Solving Linear Systems of Equations
3. Vector Space and Linear Transform
4. Orthogonality
5. Least Squares Fitting Problems
6. Eigenvalues and Eigenvectors
7. Matlab Solutions for Numerical Linear Algebra
8. Sample Space and Random Variables
9. Probability Distributions
10. Parameter Estimation
11. Principal Component Analysis
12. Linear Discriminant Analysis
13. Cluster Analysis
14. Markov Chain (optional)
15. Hidden Markov Model (optional)
16. Solving Linear Recurrence Equations (optional)
17. Huffman Tree (optional)
18. Minimum Spanning Tree (optional)
19. Traveling Salesman Problem (optional)
20. Pattern Matching Problem (optional)
21. Newton-Raphson Method for Nonlinear Systems (optional)

922 U3210

This course address software implementation issues for an embedded network device. The selected embedded platform is based on a simple and low-cost Router SoC. The software is non-OS architecture. By examing several design examples in this platform, one can see how embedded software and hardware interact together to carry out useful tasks. Special topics are also selected to give software programmers an insight into embedded system design, including digital electronics, hardware architecture, hardware interfaces, and hardware protocols. This course will cover following topics:

- Embedded Platform: Program Download, Debug Environment, Software Development Cycle, Bootloader, Flash Memory
- Embedded Hardware Design Trade-off: Cost, Performance, Complexity, Power Consumption
- Digital Electronics Overview: Transisters, MOS, Gates, Drivers, Hi-Z, Input/Output Source/Sink, Pull-up/down, Line impedance/capacitance, Power Consumption
- Embedded Hardware Architecture: System Blocks, 80251 (Dallas 390), Memory Spaces, Address/Data Busses, Interfaces, Protocols (MII, SMI, I2C)
- Embedded Software Architecture: Software Memory Map, Control Flows, Interrupts, Periodic Tasks, Non-OS Protocol Stacks (Ethernet, IP, UDP, DNS, DHCP, TCP, HTTP), and Web Server.
- Case Study: UDP, DHCP, DNS, SNTP, Embedded Web pages and CGI, Embedded TCP Client, Watch Dog Timer.