Lectures related to Channel Coding: Theory & Coding

Information Theory: Channel Capacity and Convex Functions

Explores channel capacity and convex functions in information theory, emphasizing the importance of convexity.

Covers the basics of information theory, focusing on Shannon's setting and channel transmission.

Information Theory: Entropy and Capacity

Covers concepts of entropy, Gaussian distributions, and channel capacity with constraints.

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.

Source Coding and Prefix-Free Codes

Covers source coding, injective codes, prefix-free codes, and Kraft's inequality.

Binary Coding: Channel Decoding

Explores binary channel decoding and vector spaces in coding theory.

Error Correction Codes: Theory and Applications

Covers error correction codes theory and applications, emphasizing the importance of minimizing distance for reliable communication.

Information Theory and Coding

Covers expected code word length, Huffman procedure, and entropy in coding theory.

Compression: Prefix-Free Codes

Explains prefix-free codes for efficient data compression and the significance of uniquely decodable codes.

Universal Source Coding

Covers the Lempel-Ziv universal coding algorithm and invertible finite state machines in information theory.

Communication Channels: Encoding and Decoding

Explores encoding and decoding techniques in communication systems, focusing on fundamental limits and mutual information computations.

Coding Theorem: Proof and Properties

Covers the proof and properties of the coding theorem, focusing on maximizing the properties of lx and the achievable rate.

Error Correction Codes: Basics

Introduces erasure and error channels, Hamming distance, and error correction codes.

Information Theory and Coding

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

Information Theory: Source Coding & Channel Coding

Covers the fundamentals of information theory, focusing on source coding and channel coding.

Random Coding: Achievability and Proof Variants

Explores random coding achievability and proof variants in information theory, emphasizing achievable rates and architectural principles.

Information Theory: Source Coding

Covers source coding, typical sequences, stationarity, and efficient encoding in information theory.

Information Theory Basics

Introduces information theory basics, including entropy, independence, and binary entropy function.

Secret Key Generation: Polar Coding

Explores secret key generation using polar coding for short blocklengths, discussing key capacity, rate-leakage pairs, and practical implementation.

Error Correction Codes: Decoding and Communication

Explores error correction codes, decoding algorithms, and their role in communication systems.