Information Theory and Error Control Coding

1. This Course is for Students having background in Electronics and Telecommunication or any relevant stream.

2. This Course is made from Digital Communication Point of View.

3. If you have any experience in any Communication related Courses prior to this then you can have a look.

4. The Prerequisites required are mentioned in the Course Introduction Video.

5. This is a Theoretical and Analytical Course.

6. This Course is exclusively made from Beginners point of view.

7. If you want to learn Applying Probability on Digital Communication.

8. Solutions of Each Problem will be in Detail.

8. You will be able to learn different topics with this Course like Entropy, Joint Conditional Probability, Source Coding Error Correction.

9. You will be able to Imagine this Course Visually after finishing this Course.

Information Theory and Error Correcting Codes is one of the Difficult Subjects in the Field of Electronics and Communication - You will learn it easily on this Course.

Q:- Will the course teach me Analog or Digital Communication?

A:- No, This topic is dealt in separate Course called Analog Communication and Digital Communication, and they require separate Attention all together.

With over 3+ Years of Experience and a 4.0 Instructor Rating in Udemy, I am Coming Up with Core Electronics and Communication Course of more than 4+ Hours of Theory and Problem Solving called Information Theory and Error Control Coding - Crash Course.

The curriculum was developed over a period of 4 Months.

If you are satisfied in any way, Check out my other Courses as well.

So what are you waiting for? Click the buy now button and join me on this Wonderful course.

What's inside

Learning objectives

Information theory in digital communication
Basic knowledge of information theory and error control coding

Digital communication, error correcting codes, source coding
Probability and random process

Information theory in digital communication
Basic knowledge of information theory and error control coding
Digital communication, error correcting codes, source coding
Probability and random process

Syllabus

Course Introduction

Information

Introduction

Entropy

Information Rate

Summary of Information, Entropy and Information Rate

Source Coding Techniques

Shannon Fano Coding

Hofmann Coding

Summary

Binary Channels

Conditional Probability Matrix

Joint Probability Matrix

Summary of CPM JPM

Examples on Binary Channels

Conditional and Joint Entropy

Caution Point

Mutual Information and Channel Capacity

Mutual Information

Channel Capacity

AWGN Channel

Error Control Coding

Introduction to Error Control Coding

Hamming Weight and Hamming Distance

Generator Matrix

Example on LBC

Error Detection and Error Correction of LBC

Parity Check Matrix

Caution on G and H

Syndrome Decoding

Error and Detection of Syndrome Decoding

Hamming Bound and Hamming Code

Kraft's Inequality

Special Channels

Convolution Code

Viterbi Algorithm

Repetition of Input

Repetition of Input Example

Repetition of Input Example 2

Example on Different Codes

Cyclic Redundancy Check Code (CRC Code)

Conclusion

Few Extra Points

Course Conclusion

Thank You Note

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Assumes prior knowledge of digital communication, making it suitable for students already familiar with the fundamentals in electronics and telecommunication

Designed from a beginner's point of view, which helps learners build a strong foundation in information theory and error control coding

Focuses on applying probability concepts to digital communication, which is useful for students seeking to deepen their understanding of the subject

Presents a theoretical and analytical approach, which may not suit learners who prefer hands-on or practical application-based learning

Aims to help learners visualize the concepts, which can be beneficial for those who struggle with abstract ideas in digital communication

Covers source coding and error correction, which develops core skills for students in digital communication and information theory

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Information Theory and Error Control Coding - Crash Course with these activities:

Review Probability and Random Processes

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Strengthen your understanding of probability and random processes, which are fundamental to information theory and error control coding.

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Review key concepts like probability distributions and random variables.
Work through practice problems related to probability and statistics.

Read 'Elements of Information Theory' by Cover and Thomas

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Deepen your understanding of information theory concepts with a classic textbook.

View Elements of Information Theory 2nd Edition... on Amazon

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Read the chapters related to entropy, channel capacity, and source coding.
Work through the examples and exercises in the book.

Practice Shannon-Fano and Huffman Coding

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Reinforce your understanding of source coding techniques by working through practical examples.

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Find practice datasets with varying symbol probabilities.
Apply Shannon-Fano and Huffman coding algorithms to each dataset.
Compare the efficiency of the two coding methods.

Four other activities

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Read 'Error Control Coding' by Shu Lin and Daniel J. Costello Jr.

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Expand your knowledge of error control coding with a detailed textbook.

View LDPC Code Designs, Constructions, and... on Amazon

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Focus on chapters related to linear block codes and convolutional codes.
Study the examples and derivations in the book.

Create a Visual Explanation of Viterbi Algorithm

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Solidify your understanding of the Viterbi algorithm by creating a visual aid that explains its steps.

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Research and understand the Viterbi algorithm thoroughly.
Create a diagram or animation illustrating the algorithm's operation.
Write a short explanation to accompany the visual aid.

Compile a List of Information Theory Tools and Libraries

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Create a resource list of software and libraries that can be used for information theory and error control coding tasks.

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Search for relevant tools and libraries online.
Categorize the tools based on their functionality (e.g., source coding, channel coding, simulation).
Write a brief description of each tool and its features.

Implement a CRC Error Detection System

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Apply your knowledge of CRC codes by implementing a system that detects errors in transmitted data.

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Choose a programming language and environment.
Implement the CRC encoding and decoding algorithms.
Test the system with different error patterns.

Career center

Learners who complete Information Theory and Error Control Coding - Crash Course will develop knowledge and skills that may be useful to these careers:

Telecommunications Engineer

A telecommunications engineer designs, develops, and manages communication systems. This includes work on networks, signal processing, and data transmission. This course helps build a foundation in information theory, and error control coding, which are critical aspects of digital communication. The concepts of entropy, source coding, and error correction covered in this course are essential to optimizing communication systems, making it a valuable asset to any telecommunications engineer. Understanding binary channels and error control coding techniques can help a telecommunications engineer design more robust systems.

See salaries and explore the career path for Telecommunications Engineer

Data Communication Analyst

A data communication analyst works with data transmission technologies, ensuring secure and efficient data flow. This course helps build knowledge of how digital communication works, from source coding to error correction. Understanding the concepts of entropy and various coding techniques are critical in a role like this. The material on binary channels, joint probability, and channel capacity covered in this course provide a solid foundation for anyone working in data communication analysis. The exploration of cyclic redundancy checks, and error detection techniques make this course especially relevant to this career choice.

See salaries and explore the career path for Data Communication Analyst

Research Scientist

A research scientist, particularly in fields like telecommunications or information theory, conducts research and develops new technologies and theories. This course may be useful, especially for those working on the theory of communication and error control. The analytical and theoretical focus of the course, including topics like entropy, mutual information, and channel capacity, helps build a strong foundation in this field. The in depth look at error correcting codes and techniques such as Viterbi algorithm is also relevant.

See salaries and explore the career path for Research Scientist

Wireless Communication Engineer

A wireless communication engineer specializes in the design and implementation of wireless communication systems. This course may be useful, given its focus on digital communication from the point of view of electronics and telecommunications. The course's content on topics like error control coding, channel capacity and mutual information will be relevant to any wireless communication engineer. In particular, the sections on the AWGN channel and convolutional codes, in addition to Hamming codes, provides a solid theoretical background.

See salaries and explore the career path for Wireless Communication Engineer

Academic Professor

An academic professor teaches at the university level, often conducting research in their field. This course may be useful for those who teach courses on digital communication and information theory. The topics covered by this course, including error correcting codes, entropy, and conditional probability, can deepen a professor's understanding of the subject matter. This course's focus on both theoretical concepts and problem solving may be helpful for teaching advanced communication systems.

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Network Engineer

A network engineer plans, implements, and maintains computer networks, ensuring reliable and efficient data transmission. This course may be useful for network engineers as the course provides an understanding of how information is coded and transmitted across channels, a core concept in network design. The course material covering topics such as binary channels, joint probability, and channel capacity directly relates to the challenges of managing network performance and reliability. A network engineer would benefit from the deep dive into error control coding and mutual information covered in the course.

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Embedded Systems Engineer

An embedded systems engineer designs systems that have on board computing power and functionality. These systems can range from small appliances to industrial machinery. This course may be useful as it covers the kind of coding and signal processing that is relevant to low-level communication within an embedded system. This course's discussions of source coding, error detection and correction, and topics like Hamming codes and CRC codes would be useful to an embedded systems engineer. The course explores topics like binary channels, joint probability, and channel capacity.

See salaries and explore the career path for Embedded Systems Engineer

Cryptography Specialist

A cryptography specialist develops and implements secure communication methods. This course may be useful, given the focus on information theory and error control. Concepts like entropy and coding are useful for understanding how to encode and reliably transmit data, and this is relevant to cryptography. The course's coverage of conditional probability matrix, joint probability matrix, mutual information and channel capacity is helpful.

See salaries and explore the career path for Cryptography Specialist

Signal Processing Engineer

A signal processing engineer analyzes and manipulates signals to extract useful information or improve their quality. This course may be helpful for signal processing since it deals with the fundamentals of digital communication and information theory. The course covers source coding techniques, binary channels, and error control coding techniques, all of which are applicable in signal processing. The sections on probability, entropy, and mutual information build a strong foundation in this field.

See salaries and explore the career path for Signal Processing Engineer

Information Security Analyst

An information security analyst protects computer systems and networks from security threats. While this course does not primarily focus on security, it does introduce concepts of error control and information transmission which are relevant to the field of security. Knowing how data is encoded and transmitted helps anyone working on data security. This course's deep dive into source coding, binary channels, and error correcting codes can provide valuable background knowledge. Though not a direct focus, this course may help any information security analyst better understand data transmission protocols.

See salaries and explore the career path for Information Security Analyst

Software Developer

A software developer writes, tests, and maintains software. This course may be helpful for software developers that work on communication protocols. Knowledge of error correction and data transmission techniques would be useful in that area. This course covers topics such as source coding, binary channels, and error control coding, which are relevant to building robust communication systems. Software developers may find the topics on joint probability and channel capacity useful. This course may be useful to those who work with software designed for digital communication.

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Systems Analyst

A systems analyst researches and recommends solutions that integrate an organization’s hardware, software, and other technologies. This course may be useful for understanding the data transmission techniques underlying a system or network. A systems analyst benefits from a strong foundation in information theory and error control, given their need to understand how data is transmitted and processed. While not a direct fit, this course's topics on digital communication, source coding and error correction can inform the analyst's recommendations, particularly when dealing with data transmission systems.

See salaries and explore the career path for Systems Analyst

Data Scientist

A data scientist extracts meaningful insights from data. This course may be useful for data scientists that deal with noisy datasets as the course explores the concepts of error detection and correction. This course's coverage on topics such as entropy, conditional probability and joint probability is helpful to anyone working with probabilistic models and datasets. Though it may not be a perfect fit, it may help a data scientist working with communication data to better understand the noise that is present.

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Technical Writer

A technical writer produces documentation about technical subjects, such as software or hardware. This course may be useful for a technical writer who documents communication systems. This course's focus on information theory, digital communication, and error correcting codes can provide a deeper understanding of the technologies being documented. The course may inform a technical writer particularly when the writer is dealing with the challenges of data transmission and coding. The technical writer can then better explain these ideas.

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Technical Support Specialist

A technical support specialist helps users troubleshoot and resolve issues with technical products or systems. This course may be useful for anyone working in a telecommunications or networking context who needs to understand the basics of signal transmission. This course covers topics such as source coding, binary channels, and error control coding, which are relevant to the underlying technologies. The course may provide a technical support specialist with useful background knowledge. A technical support specialist may find the material regarding conditional and joint entropy especially informative.

See salaries and explore the career path for Technical Support Specialist

Information Theory and Error Control Coding - Crash Course

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