Information Theory & Coding EE 7th Sem Syllabus for AKTU B.Tech 2019-20 Scheme (Departmental Elective-III)

Information Theory & Coding detail syllabus for Electronics Engineering (EE), 2019-20 scheme is taken from AKTU official website and presented for AKTU students. The course code (REC071), and for exam duration, Teaching Hr/Week, Practical Hr/Week, Total Marks, internal marks, theory marks, and credits do visit complete sem subjects post given below.

For all other ee 7th sem syllabus for b.tech 2019-20 scheme aktu you can visit EE 7th Sem syllabus for B.Tech 2019-20 Scheme AKTU Subjects. For all other Departmental Elective-III subjects do refer to Departmental Elective-III. The detail syllabus for information theory & coding is as follows.

Unit I

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Unit II

Asymptotic Equipartition Property: Asymptotic Equipartition Property Theorem, Consequences of the AEP: Data Compression, High-Probability Sets and the Typical Set Data Compression: Examples of Codes, Kraft Inequality, Optimal Codes, Bounds on the Optimal Code Length, Kraft Inequality for Uniquely Decodable Codes, Huffman Codes, Some Comments on Huffman Codes, Optimality of Huffman Codes, Shannon-Fano-Elias Coding

Unit III

Channel Capacity: Examples of Channel Capacity, Symmetric Channels, Properties of Channel Capacity, Preview of the Channel Coding Theorem, Definitions, Jointly Typical Sequences, Channel Coding Theorem

Unit IV

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Unit V

Convolution codes Encoding convolutional codes, Generator matrices for convolutional codes, Generator polynomials for convolutional codes, Graphical representation of convolutional codes, Viterbi decoder

Course Objectives:

1. To learn basic of Entropy.
2. To learn Asymptotic Equipartition Property.
3. To learn Channel Capacity.
4. To learn the implementation of Block Codes
5. To learn the Convolution codes

Course Outcomes:

• Model the Entropy, Joint Entropy and Conditional Entropy, Relative Entropy and Mutual Information, Relationship Between Entropy and Mutual Information
• Design Data Compression, Examples of Codes, Kraft Inequality, Optimal Codes, Bounds on the Optimal Code Length
• Identify the Examples of Channel Capacity, Symmetric Channels, Properties of Channel Capacity, Preview of the Channel Coding Theorem.
• Analyse Introduction to block codes, Single-parity-check codes, Product codes, Repetition codes, Hamming codes
• Design Generator matrices for convolutional codes, Generator polynomials for convolutional codes

Reference Books:

1. Bose, Inforrmation Theory, Coding and Cryptography, Mcgrawhill Education
2. Joy A. Thomas, Thomas M. Cover, Elements of information theory, Wiley-Interscience; 2edition (July 18, 2006)
3. S. Gravano, Introduction to Error Control Codes OUP Oxford (24 May 2001)
4. Robert B. Ash, Information Theory, Dover Publications (November 1, 1990)
5. Todd k Moon, Error Correction Coding: Mathematical Methods and Algorithms Wiley,2005.

For detail syllabus of all other subjects of B.Tech Ee, 2019-20 regulation do visit Ee 7th Sem syllabus for 2019-20 Regulation.

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