Transmission of information over noisy channels. Measures of information and transmission channel capacity. Use of codes to improve the reliability of such transmission. Mathematical theory of information. Transmission at rates above channel capacity. Includes linear codes, error detecting and correcting codes, Hamming codes.
Electrical engineering graduate students who wish to pursue research or careers in the data communications field require the course to understand the performance limits of this field. Communications research also requires a basic knowledge of data transmission through noise channels.
Prerequisites: 4634, 5605, STAT 4714
This course sequence requires a basic understanding of probability theory, stochastic processes and digital communication theory. The probability theory may be obtained in STAT 4714, the stochastic processes may be obtained in 5605, and the digital communication theory may be obtained in 4634.
Percentage of Course
|Probability of Error and Information Measurement||15%|
|Channel Capacity, Kraft Inequality||10%|
|Data Compaction, Entropy, Markov Sources, Shannon’s Theorem||10%|
|Error and performance Channel Bounds||10%|
|Noisy Channels, Mutual Information, Capacity of Discrete Noisy Channels||20%|