Lectures related to Designing Convolutional Codes

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

Covers Soft-Output MIMO Detection for BICM, LLRs computation, BICM system model, and challenges of channel assumptions.

Explains quantum correction codes using two classic codes to correct errors, focusing on goal flips and headlight flips.

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

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

Covers the solution and common mistakes in Assignment 1a on system design.

Covers source coding, cryptography, and channel coding for communication systems.

Covers the concept of compression and constructing prefix-free codes based on given information.

Explores the Hamming Code for error correction, emphasizing its ability to correct single-bit errors.