Module Title:   Information Theory and Data Communication

Module Credit:   20

Module Code:   CM-0439D

Academic Year:   2015/6

Teaching Period:   Semester 1

Module Occurrence:   A

Module Level:   FHEQ Level 7

Module Type:   Standard module

Provider:   Computer Science

Related Department/Subject Area:   School of Electrical Engineering & Computer Science

Principal Co-ordinator:   Dr Taufiq Asyhari

Additional Tutor(s):   -

Prerequisite(s):   None

Corequisite(s):   None

Aims:
The aim of this module is to introduce and apply basic principles of information theory for data communication. The focus is on concepts and techniques for reliably transmitting and efficiently processing data.

Learning Teaching & Assessment Strategy:
A series of lectures will provide the essential theories and concepts. Laboratory sessions will provide practical applications of the concepts. Oral feedback is given during the practical classes as appropriate. Module assessment consists of two coursework exercises aimed to test skills, knowledge and understanding on theoretical concepts to solve relevant practical problems. The supplementary assessment follows the coursework format to address deficiencies encountered at the first attempt.

Lectures:   24.00          Directed Study:   152.00           
Seminars/Tutorials:   0.00          Other:   0.00           
Laboratory/Practical:   24.00          Formal Exams:   0.00          Total:   200.00

On successful completion of this module you will be able to...

i. Gain practical understanding of how data can be quantitatively measured, and effectively processed and communicated using information-theoretic principles;
Ii. Demonstrate knowledge and general understanding on the fundamental limits for data communication and a number of factors affecting the reliability of data communication.

On successful completion of this module you will be able to...

i. Demonstrate knowledge of information-theoretic principles underlying any data compression and communication systems;
Ii. Apply the principles to design efficient compressor/decompressor and reliable transmission schemes for data communication.

On successful completion of this module you will be able to...

i. Acquire confidence in applying rigorous analytical approaches to assess problems in random environments.
Ii. Deploy efficient time-management and problem formulation and solving skills to solve complex practical problems.
Iii. Write and communicate in concise, clear and coherent manner.

  Coursework   50%
 
  Coursework 1 (individual) - Exercises on data compression and algorithms.
  Coursework   50%
 
  Coursework 2 (group) - Exercises on data transmission
  Coursework   100%
 
  Supplementary coursework assessment (individual coursework)

Outline Syllabus:
1. Introduction. 2. Review of probability and statistics. 3. Elements of information theory and data communication. 4. Data compression and algorithms. 5. Data transmission. 6. Techniques for data storage and security systems.

Reading List:
Sommaruga, G. (2009) Formal theories of information: From Shannon to semantic information theory and general concepts of information, Berlin: Springer-Verlag.
Biggs, N. L. (2008) Codes: An introduction to information communication and cryptography, London: Springer-Verlag.
Gallager, R. G. (2008) Principles of Digital Communication, New York: Cambridge University Press.
Cover, T. and Thomas, J. A. (2006) Elements of information theory, Hoboken, New Jersey: John Wiley & Sons.
Bruen, A. A. and Forcinito, M. A. (2005) Cryptography, information theory, and error-correction, a handbook for the 21st century, Hoboken, New Jersey: John Wiley & Sons.
MacKay, D. J. C. (2003) Information theory, inference, and learning algorithms, Cambridge: Cambridge University Press.

Version No:  1