ELG 5170 Information Theory

3 units
Electrical Engineering
Faculty of Engineering
Measure of information: entropy, relative entropy, mutual information, asymptotic equipartition property, entropy rates for stochastic processes; Data compression: Huffman code, arithmetic coding; Channel capacity: random coding bound, reliability function, Blahut-Arimoto algorithm, Gaussian channels, colored Gaussian noise and "water-filling"; Rate distortion theory; Network information theory. This course is equivalent to EACJ 5501 at Carleton University.

Components:

Lecture

Previously Offered Terms:

Fall
Winter
All Professors
A Average (8.778)
Most Common: A- (39%)
18 students

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NS

F

D

C

B

A-

A+

Mark Chua

Winter 2023 - W00

A Average (9.182)
Most Common: A+ (55%)
11 students

P

S

NS

F

D

C

B

A-

A+

Yongyi Mao

2 sections from Fall 2017 to Fall 2018

A- Average (8.143)
Most Common: A- (86%)
7 students

P

S

NS

F

D

C

B

A-

A+