课程名称 (Course Name) ：Coding and Information Theory
课程代码 (Course Code）： X033532/CS28008
学分/学时 (Credits/Credit Hours)： 3/48
开课时间 (Course Term )： Autumn: September- January (next year)
开课学院（School Providing the Course）:
School of Electronics, Information and Electrical Engineering (SEIEE)
任课教师（Teacher）: Yuan Luo
课程讨论时数（Course Discussion Hours）: 48
课程实验数（Lab Hours）: 0
课程内容简介(Course Introduction):
Information and Coding Theory has fundamental contributions to communication theory (data transmission etc.), computer science (data compression etc.), network, cryptography, statistical physics and so on.
This course has two parts. The first part is of information theory, which includes the measurement of information (entropy, relative entropy, mutual information); weakly typical sequence (for data compression); strongly typical sequence (for data transmission); and Shannon Theorem. The second is of coding theory, which includes linear codes, cyclic codes, Hamming codes, RS codes, Arithmetic code, LDPC code, decoding principles etc. Furthermore, some basic knowledge about finite field and probability theory will be reviewed.
教学大纲(Course Teaching Outline):
1．Fundamental Information Theory Knowledge: Markov Chain, Information Measurement, Entropy, Mutual Information, Chain Rules, Basic Inequalities
2．Source Coding: Week Typical Set, Source Coding Theorem, Huffman Code, Arithmetic code, Lempel-Ziv Algorithm,…
3. Channel Communication: Channel Capacity, Channel Coding Theorem
4. Finite Fields: Basic Definition, Structure Theorems
5. Error Control Coding: Decoding Principles, Combinatorial Bounds, Hamming Code, Cyclic Code, RS code, LDPC code, Convolution code, …
课程进度计划(Course Schedule):
1．Fundamental Information Theory Knowledge: the 2nd -4th week (9 credit hours)
2．Source Coding: the 5th-7th week (9 credit hours)
3. Channel Communication: the 8th-10th week (9 credit hours)
4. Finite Fields: the 11th -13th week (9 credit hours)
5. Error Control Coding: the 14th-17th week(12 credit hours)
课程考核要求(Course Assessment Requirements)：
Final examination 70%; roll call 10%; homework 20%.
参考文献(Course References)：
1. Information Theory, Coding and Cryptography, 2nd Edt., R. Bose, McGraw-Hill, 2008.
2. Information Theory and Network Coding, R. W. Yeung, Springer, 2008.
3. Elements of Information Theory, T. M. Cover and J. A. Thomas, John Wiley and Sons, 1991.
4. The Theory of Error-Correcting Codes, 6th printing, F.J. MacWilliams and N.J.A. Sloane, Elsevier Science Publishers,1988.
5. The Theory of Information and Coding, 2nd edition, R. J. McEliece, CambridgeUniv.Press, 2002.
预修课程（Prerequisite Course）
Probability Theory
Linear Algebra
