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MTHE 474  Information Theory  Units: 3.50  
Topics include: information measures, entropy, mutual information, modeling of information sources, lossless data compression, block encoding, variable-length encoding, Kraft inequality, fundamentals of channel coding, channel capacity, rate-distortion theory, lossy data compression, rate-distortion theorem.
(Lec: 3, Lab: 0, Tut: 0.5)
Requirements: Prerequisites: STAT 251 or MTHE 351 or ELEC 326 Corequisites: Exclusions:  
Offering Term: F  
CEAB Units:    
Mathematics 6  
Natural Sciences 0  
Complementary Studies 0  
Engineering Science 23  
Engineering Design 13  
Offering Faculty: Faculty of Arts and Science  

Course Learning Outcomes:

  1. Computing Shannon's information measures (entropy, Kullback-Leibler distance and mutual information).
  2. Computing the capacity of communication channels.
  3. Reasoning about the properties of Shannon's information measures (entropy, Kullback-Leibler distance and mutual information).
  4. Using mathematical tools to infer properties of coding and communication systems.
  5. Probabilistic modeling of communication systems for source and channel coding purposes.
  6. Using tools from probability theory to analyze communication systems.
  7. Metric assessment of data compression code designs.