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Course number and title: EE231A Information Theory: Channel and Source Coding
Credits: 4
Instructor(s)-in-charge: L. Dolecek (dolecek@ee.ucla.edu)
Course type: Lecture
Required or Elective: A Signals and Systems course.
Course Schedule:
Lecture: 4 hrs/week.
Outside Study: 7 hrs/week.
Office Hours: 2 hrs/week.
 
Course Assessment:
Homework: Several homework assignments.
Exams: 1 midterm and 1 final examination.
 
Grading Policy: Typically, Homework: 20%, Midterm 30%, Final 50%.
Course Prerequisites: EE131A.
Catalog Description: Fundamental limits on compression and transmission of information. Topics include limits and algorithms for lossless data compression, channel capacity, rate versus distortion in lossy compression, and information theory for multiple users.  
Textbook and any related course material:
Elements of Information Theory by Thomas Cover and Joy Thomas.
 
Course Website
Topics covered in the course:
Definitions of entropy, relative entropy, mutual information and related equalities and inequalities.
Asymptotice equipartition Property (AEP).
Entropy rate of a stochastic process.
Lossless compression: Kraft inequality, Huffman algorithm, arithmetic decoding.
Computation of channel capacity for discrete memoryless channels. Proof of Shannon's coding theorem.
Differential Entropy.
Gaussian Channel Capacity.
Rate-Distortion Theory: Computing the R(D) curve and proof of the Rate Distortion Theorem.
Multiple Access Channels, Slepian Wolf encoding.
Maximum Entropy Distributions.
Will this course involve computer assignments? NO Will this course have TA(s) when it is offered? NO

:: Last modified: August 2011 by C. E. Chiuco ::

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