M Tech (Computer Science and Applications):Information and Coding Theory

Thapar University
In Patiala

Price on request
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Important information

  • Master
  • Patiala

Important information

Where and when

Starts Location
On request
Thapar University P.O Box 32, 147004, Punjab, India
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Frequent Asked Questions

· Requirements

Admission to M. Tech. (Computer Science and Applications) will be open to a candidate who obtains at least 50% marks in aggregate in the qualifying examination from a recognized university.

Course programme

Semester I

Advanced Data Structures
Data Communication and Computer Networks
Computer Organization and Operating Systems
Computational Algorithms in Optimization
Statistical Methods and Algorithms
Database Management and Administration

Semester II

Object Oriented Analysis and Design
Software Engineering
Logic and its applications
Computer Graphics and Multimedia Technologies
Web Technologies and E-Governance

Semester III

Thesis (starts)

Semester IV

Thesis (contd.)

Information and Coding Theory

Information Theory: Entropy of a source, mutual information, chain rules, Units of entropy, Entropy of a random variable, properties of entropy, Asymptotic Equipartition Property (AEP), Entropy of random processes, Noiseless coding-variable length encoding-strings and codes, Fixed and variable length codes, Unique decipherability, Kraft’s theorem, McMillan theorem, Huffman encoding, Arithmetic Coding, Noiseless coding theorem, Noisy Coding– Discrete memoryless channels and conditional entropy, Mutual information and channel capacity, Noisy coding theorem, Error correcting codes, Rate Distortion, Quantization, Converse of rate distortion function.

Coding Theory: Error correction and Detection, Minimum distance decoding, Linear codes- Generator matrix, Dual of a linear code, syndrome decoding, Non-linear codes-, Hamming codes, Reed-Muller codes, Finite fields, BCH codes, Cyclic codes-generator polynomial of a cyclic code, Idempotent generator of a cyclic code, Minimal cyclic code, Maximum distance separable codes.

Laboratory: The lab work will be based on the implementation of noisy and noiseless coding algorithms, error correction techniques and error detection techniques.

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