Convolutional Codes: Basics and Applications

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Related lectures (34)

Convolutional Codes: Decoding and Performance Analysis

Covers the decoding and performance analysis of convolutional codes in communication systems.

Convolutional Codes: Mapping Symbols and Paths

Covers Convolutional Codes, focusing on mapping symbols and paths.

Convolutional Codes: Encoding and Decoding

Explains the encoding and decoding process of convolutional codes using constellation prints.

Convolutional Codes: Decoding and Eye Diagrams

Covers the decoding process of convolutional codes and the analysis of eye diagrams.

Linear Codes: Systematic vs Non-Systematic

Explores the creation of systematic linear codes and the transformation of non-systematic codes, showcasing their equivalence and importance in simplifying encoding and decoding processes.

Convolutional Coder Introduction

Covers the introduction of Convolutional Coder, explaining its structure and operation.

Designing Convolutional Codes

Covers the art of designing convolutional codes to improve communication rate.

Convolutional Codes: Analysis and Applications

Delves into the analysis and applications of convolutional codes, highlighting the significance of correct implementation for optimal results.

Linear Codes: Dimension and Hamming Weight

Discusses linear codes' dimension and Hamming weight with examples and theorems.

Information Coding: Source, Cryptography, Channel

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

Error Correction Codes: Decoding and Communication

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

Error Correction Codes: Hamming Code

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

Binary Coding: Channel Decoding

Explores binary channel decoding and vector spaces in coding theory.

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.

Error Correction Codes: Theory and Applications

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

Minimum Distance Decoding

Explains Minimum Distance (MD) decoding on erasure channels with illustrative examples.

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.

Reed-Solomon Codes: Construction and Properties

Explores Reed-Solomon codes' construction, properties, decoding examples, linear codes, and applications in error correction on optical disks.

Lecture: Shannon

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

Linear Block Codes: Basics

Covers the basics of linear block codes and systematic codes over a field F.

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