教學大綱表 (111學年度 第2學期)
請遵守智慧財產權，勿使用非法影印教科書，避免觸法。
課程名稱
Course Title		 (中文) 資訊壓縮與錯誤更正
(英文) Data Compression And Error Correction 		開課單位
Departments		 資訊工程學系
課程代碼
Course No.		 I4540
授課教師
Instructor		 張薰文
學分數
Credit		 3.0 必/選修
core required/optional		 選修 開課年級
Level		 大四
先修科目或先備能力(Course Pre-requisites)：
課程概述與目標(Course Overview and Goals)：資料壓縮的目的在於減少傳送時間與儲存需求，本課程將介紹壓縮技術的分類、原理與評量。
教科書(Textbook) K. Sayood, Introduction to Data Compression, 4th ed., Morgan Kaufmann, 2012.
參考教材(Reference) S. Lin and D. J. Costello, Error Control Coding, 2nd ed., Prentice Hall, 2004.
課程大綱 Syllabus 學生學習目標
Learning Objectives		 單元學習活動
Learning Activities		 學習成效評量
Evaluation		 備註
Notes
序
No.		 單元主題
Unit topic		 內容綱要
Content summary
1 Introduction 1. Compression Techniques
2. Modeling and Coding 		1. Compression Techniques
2. Modeling and Coding		  
2 Mathematical Preliminaries for Lossless Compression 1. Introduction to Information Theory
2. Models
3. Coding 		1. Introduction to Information Theory
2. Models
3. Coding		  
3 Mathematical Preliminaries for Lossless Compression 1. Introduction to Information Theory
2. Models
3. Coding 		1. Introduction to Information Theory
2. Models
3. Coding		  
4 Huffman Coding 1. Huffman Coding Algorithm
2. Nonbinary Huffman Codes
3. Adaptive Huffman Coding
4. Applications of Huffman Coding 		1. Huffman Coding Algorithm
2. Nonbinary Huffman Codes
3. Adaptive Huffman Coding
4. Applications of Huffman Coding		  
5 Huffman Coding 1. Huffman Coding Algorithm
2. Nonbinary Huffman Codes
3. Adaptive Huffman Coding
4. Applications of Huffman Coding 		1. Huffman Coding Algorithm
2. Nonbinary Huffman Codes
3. Adaptive Huffman Coding
4. Applications of Huffman Coding		  
6 Arithmetic Coding 1. Coding a Sequence
2. Generating a Binary Code
3. Adaptive Arithmetic Coding 		1. Coding a Sequence
2. Generating a Binary Code
3. Adaptive Arithmetic Coding		  
7 Arithmetic Coding 1. Coding a Sequence
2. Generating a Binary Code
3. Adaptive Arithmetic Coding 		1. Coding a Sequence
2. Generating a Binary Code
3. Adaptive Arithmetic Coding		  
8 Mathematical Preliminaries for Lossy Compression 1. Distortion Criteria
2. Rate Distortion Theory
3. Models 		1. Distortion Criteria
2. Rate Distortion Theory
3. Models		  
9 Mathematical Preliminaries for Lossy Compression 1. Distortion Criteria
2. Rate Distortion Theory
3. Models 		1. Distortion Criteria
2. Rate Distortion Theory
3. Models		  
10 Scalar Quantization 1. Quantization problem
2. Uniform Quantizer
3. Adaptive Quantization
4. Nonuniform Quantization
5. Entropy-Coded Quantization 		1. Quantization problem
2. Uniform Quantizer
3. Adaptive Quantization
4. Nonuniform Quantization
5. Entropy-Coded Quantization		  
11 Scalar Quantization 1. Quantization problem
2. Uniform Quantizer
3. Adaptive Quantization
4. Nonuniform Quantization
5. Entropy-Coded Quantization 		1. Quantization problem
2. Uniform Quantizer
3. Adaptive Quantization
4. Nonuniform Quantization
5. Entropy-Coded Quantization		  
12 Scalar Quantization 1. Quantization problem
2. Uniform Quantizer
3. Adaptive Quantization
4. Nonuniform Quantization
5. Entropy-Coded Quantization 		1. Quantization problem
2. Uniform Quantizer
3. Adaptive Quantization
4. Nonuniform Quantization
5. Entropy-Coded Quantization		  
13 Vector Quantization 1. Vector v.s. Scalar Quantization
2. The LBG Algorithm
3. Structured Vector Quantization 		1. Vector v.s. Scalar Quantization
2. The LBG Algorithm
3. Structured Vector Quantization		  
14 Vector Quantization 1. Vector v.s. Scalar Quantization
2. The LBG Algorithm
3. Structured Vector Quantization 		1. Vector v.s. Scalar Quantization
2. The LBG Algorithm
3. Structured Vector Quantization		  
15 Differential Encoding 1. Basic Algorithm
2. Prediction in DPCM
3. Adaptive DPCM 		1. Basic Algorithm
2. Prediction in DPCM
3. Adaptive DPCM		  
16 Differential Encoding 1. Basic Algorithm
2. Prediction in DPCM
3. Adaptive DPCM 		1. Basic Algorithm
2. Prediction in DPCM
3. Adaptive DPCM		  
17 Mathematical Preliminaries for Transforms, Subbands, and Wavelets 1. Vector Spaces
2. Fourier Series and Fourier Transformation
3. Linear Systems 		1. Vector Spaces
2. Fourier Series and Fourier Transformation
3. Linear Systems		  
18 Mathematical Preliminaries for Transforms, Subbands, and Wavelets 1. Vector Spaces
2. Fourier Series and Fourier Transformation
3. Linear Systems 		1. Vector Spaces
2. Fourier Series and Fourier Transformation
3. Linear Systems		  
19 Applications 1. Image Coding
2. Audio Coding
3. Speech Coding 		1. Image Coding
2. Audio Coding
3. Speech Coding		  


教學要點概述：
1.自編教材 Handout by Instructor：
□ 1-1.簡報 Slids
□ 1-2.影音教材 Videos
□ 1-3.教具 Teaching Aids
□ 1-4.教科書 Textbook
□ 1-5.其他 Other
□ 2.自編評量工具/量表 Educational Assessment
□ 3.教科書作者提供 Textbook

成績考核 Performance Evaluation： 期末考：30%   期中考：30%   平時考：40%  

教學資源(Teaching Resources)：
□ 教材電子檔(Soft Copy of the Handout or the Textbook)
□ 課程網站(Website)
扣考規定：http://eboard.ttu.edu.tw/ttuwebpost/showcontent-news.php?id=504