Lecture Time and Location

Tuesday, 6:30PM - 9:20PM. Curtis 453.

Instructor

Prof. John MacLaren Walsh. Office: Bossone 203. Telephone: (215) 895-2360. Email: jwalsh@ece.drexel.edu

Office Hours: Tuesday 5:30PM-6:30PM.

Course Website

This class has a website: http://www.ece.drexel.edu/walsh/ecet602/ecet602.html. You will need to check it periodically throughout the semester for information concerning reading assignments, homework assignments, exam information, and projects.

Prerequisites

Courses covering probability and random variables such as ECES-521 and ECES-522.

Textbooks and Resources

Throughout the quarter we will make use of material from the following texts (and others), which you may loan from the instructor or library:

• Elements of Information Theory, J. Thomas and T. Cover.
• Information Theory and Network Coding, R. W. Yeung
• Information Theory, Inference, and Learning Algorithms, D. J. C. MacKay
• Error Control Coding, S. Lin and D. Costello.
• Error Control Systems for Digital Communication and Storage, S. Wicker
• Modern Coding Theory, T. Richardson, R. Urbanke

Much of the material will closely follow sections from the first and fourth book above, which you can purchase from the bookstore. The primary “text” for the course will be the Course Lecture Notes which will be available in class and online (see schedule below).

Grading Policy

There will be graded homework assignments, a midterm exam, a final project, and a final exam. These will count towards the final grade as follows: homework (25%), midterm exam (25%), final exam (25%), final project (25%). Due to the few, yet condensed, nature of the lectures, late homework can not be accepted. If you wish to dispute the grading of a homework/project/exam, you must attach to the homework/project/exam a piece of paper outlining your complaint and return it to the instructor within 2 business days after the homework/project/exam is returned. Any disputation of grading which does not follow these guidelines will not be accepted, and may lead to a reduction in your grade.

Tentative Outline of Course Content

This class covers an advanced graduate level blend of information theory, compression, and channel coding techniques. A tentative course outline, subject to revision as we proceed, is attached below.

• Information Theory Essentials
  • Typical Sequences
  • Channel Capacity
  • Source Coding (Lossless and Lossy)
  • Source Channel Coding Separation Theorem
• Practical Compression
  • Huffman Codes
  • Universal Source Codes. Lempel-Ziv.
  • Practical Multimedia Lossy Compression. Transform Codes.
• Channel Codes
  • Linear Block Codes
  • Reed Solomon Codes
  • Convolutional Codes
  • Turbo Codes & Low-Density Parity-Check Codes

Course Schedule

• Typical Sequences & Channel Capacity Achievability & Converse (March 31, 2015)
• Lossless Compression (April 7, 2015)
• Lossy Compression Theory - Converse & Achievability (April 14, 2015)
• Source Channel Separation Theorem (April 21, 2015)
• Midterm Exam (May 5, 2015)
• Classical Channel Coding, I: Galois Fields, Basic Linear Block Codes (May 12, 2015)
• Classical Channel Coding, II: Cyclic Codes, BCH Codes, RS Codes (May 19, 2015)
• Modern Channel Codes: Convolutional Codes, Turbo Codes & Low-Density Parity-Check Codes (May 26, 2015)
• Practical Source Codes (June 2, 2015)
• Final Exam (June 9, 2015)

Assignment Schedule

This will be updated periodically throughout the semester, and is thus subject to change.

• April 14: Homework 1 due in class.
• April 21:Homework 2 due in class.
• April 28: Homework 3 due. Extension: hand in by Friday, May 1.
• May 5: Midterm exam.
• May 26: Combined Homeworks 4& 5 due in class.
• June 2: Work on the final project.
• June 9: Final Exam. Also, work on the Final Project due at the beginning of the final exam.

This document is current as of May 19, 2015.