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Introduction
Data compression is an integral part of data transmission, storage and
processing. We cover different data compression techniques, in the
lossless and lossy compression categories, with respect to different types of
data such as text, audio, and video data under specific application
circumstances or requirements. We introduce the basic theory by Shannon for
information encoding, and recent advances in mathematical and algorithmic aspects of data compression.
We emphasize on application problems and efficient implementation issues. We
give an overview of sound, image and frame-based (MPEG-1/2/4, H.261/3/L) and
object-based (e.g. MPEG-4) video coding standards.
Prerequisite
Calculus, Linear Algebra, Basic Statistics, Programming Methodology
Textbook
By the end of the semester, a review of the text book
will be available.
Primary reading: C. E. Shannon and Information Theory
- Claude
E. Shannon and Information Theory Scientific American article (Oct 14,
2002)
- Shannon's "A
Mathematical Theory of Communication" originally appeared on
The Bell System Technical Journal, Vol. 27, 1948 (required for grad
students)
Problem sets and term project
 | Problem sets will be assigned, approximately every two weeks, along with
the introduction of new problems, concepts and algorithms |
 | The term project consists of a problem-solution description, a software
implementation and a formal in-class presentation. The project can be
developed individually or within a two-persons team. A list of projects
will be suggested in class or proposed by students. |
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