EE/Ma/CS/IDS 136 - Information Measures and Applications

This class introduces information measures such as entropy, information divergence, mutual information, information density, and establishes the fundamental importance of those measures in data compression, statistical inference, and error control. The course does not require a prior exposure to information theory; it is complementary to EE 126a. Not offered 2025-26.