Information Theory
ENG-SCI 250
Subject & Catalog Number
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Course Information
Description
Fundamental concepts of information theory, Entropy, Kullback-Leibler divergence, Mutual information; typical sequences and their applications, Loss-less data compression, Huffman codes, Elias Codes, Arithmetic Codes, Discrete Memory-less Channels, Channel Coding and Capacity, Differential Entropy, Gaussian Channels, rate distortion theory, Multi-user Information Theory, Connections between information theory and statistics.
Recommended Prep
Engineering Sciences 150 or knowledge of basic probability.
School
Faculty of Arts & Sciences
Credits
4
Cross Reg
Available for Harvard Cross Registration
Department
Engineering Sciences
Course Component
Lecture
General Education
N/A
Quantitative Reasoning with Data
N/A
Divisional Distribution
Science & Engineering & Applied Science
Course Level
Primarily for Graduate Students
