# InfoCoBuild

## An Introduction to Coding Theory

An Introduction to Coding Theory. Instructor: Dr. Adrish Banerjee, Department of Electrical Engineering, IIT Kanpur. Error control coding is an indispensable part of any digital communication system. In this introductory course, we will discuss theory of linear block codes and convolutional codes, their encoding and decoding techniques as well as their applications in real world scenarios. Starting from simple repetition codes, we will discuss among other codes: Hamming codes, Reed Muller codes, low density parity check codes, and turbo codes. We will also study how from simple codes by concatenation we can build more powerful error correcting codes. (from nptel.ac.in)

 Lecture 22 - Problem Solving Session V

In this lecture we will solve problems related to feedforward inverse of convolutional encoders. We will describe the condition for existence of a feedforward inverse of a convolutional encoder. Further, we will show that catastrophic encoders do not have a feedforward inverse. Finally, we will prove a property related to an important distance measure (column distance function) for convolutional codes.

Go to the Course Home or watch other lectures:

 Lecture 01 - Introduction to Error Control Coding, Part I Lecture 02 - Introduction to Error Control Coding, Part II Lecture 03 - Introduction to Error Control Coding, Part III Lecture 04 - Introduction to Linear Block Codes, Generator Matrix and Parity Check Matrix Lecture 05 - Syndrome, Error Correction and Error Detection Lecture 06 - Problem Solving Session I Lecture 07 - Coding of Linear Block Codes Lecture 08 - Distance Properties of Linear Block Codes I Lecture 09 - Distance Properties of Linear Block Codes II Lecture 10 - Problem Solving Session II Lecture 11 - Some Simple Linear Block Codes I Lecture 12 - Some Simple Linear Block Codes II: Reed Muller Codes Lecture 13 - Bounds on the Size of a Code Lecture 14 - Problem Solving Session III Lecture 15 - Introduction to Convolutional Codes I: Encoding Lecture 16 - Introduction to Convolutional Codes II: State Diagram, Trellis Diagram Lecture 17 - Convolutional Codes: Classification, Realization Lecture 18 - Convolutional Codes: Distance Properties Lecture 19 - Decoding of Convolutional Codes I: Viterbi Algorithm Lecture 20 - Decoding of Convolutional Codes II: BCJR Algorithm Lecture 21 - Problem Solving Session IV Lecture 22 - Problem Solving Session V Lecture 23 - Performance Bounds for Convolutional Codes Lecture 24 - Low Density Parity Check Codes Lecture 25 - Decoding of Low Density Parity Check Codes I Lecture 26 - Decoding of Low Density Parity Check Codes II: Belief Propagation Algorithm Lecture 27 - Turbo Codes Lecture 28 - Turbo Decoding Lecture 29 - Problem Solving Session VI Lecture 30 - Distance Properties of Turbo Codes Lecture 31 - Convergence of Turbo Codes Lecture 32 - Automatic Repeat reQuest (ARQ) Schemes Lecture 33 - Applications of Linear Codes