Information Theory: Channel Capacity and Convex Functions

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Convex Functions

Covers the properties and operations of convex functions.

Biological Randomness and Data Analysis

Explores randomness in biology, covering thermal fluctuations, random walks, and data analysis techniques.

Information Theory and Coding

Covers source coding, Kraft's inequality, mutual information, Huffman procedure, and properties of tropical sequences.

Information Measures

Covers information measures like entropy and Kullback-Leibler divergence.

Convex Optimization: Convex Functions

Covers the concept of convex functions and their applications in optimization problems.

Chain Rule for Entropy

Explores the chain rule for entropy, decomposing uncertainty in random variables and illustrating its application with examples.

Geodesic Convexity: Theory and Applications

Explores geodesic convexity in metric spaces and its applications, discussing properties and the stability of inequalities.

Variational Formulation: Information Measures

Explores variational formulation for measuring information content and divergence between probability distributions.

Optimization Programs: Piecewise Linear Cost Functions

Covers the formulation of optimization programs for minimizing piecewise linear cost functions.

Information Theory: Source Coding, Cryptography, Channel Coding

Covers source coding, cryptography, and channel coding in communication systems, exploring entropy, codes, error channels, and future related courses.