These notes provide a graduate-level introduction to the mathematics of Information Theory. Purdue University, 610 Purdue Mall, West Lafayette, IN, 47907, 765-494-4600 Source coding techniques such as scalar and vector quantization, orthogonal transforms, and linear prediction are introduced and their performance is analyzed theoretically.
ECE 64200 - Information Theory and Source Coding Credits: 3 Areas of Specialization(s): Communications, Networking, Signal & Image Processing.
and ECE4606.Afterwards, the course will consider error control coding
Tom Richardson and Rüdiger Urbanke, Modern Coding Theory, Cambridge University Press, 2008.
to develop source coding algorithms,- develop source coding schemes for lossless coding, like Huffman coding, arithmetic coding, Lempel-Ziv coding, universal source coding,- develop source coding schemes for lossy coding, like scalar and vector quantization, Lloyd-Max quantization, entropy-constrained quantization, high-rate quantization, transform coding, predictive coding,- implement (for example with MatLab) and assess the developed source coding schemes / algorithms, - explain coding design choices using the principles of information theory,- develop source coding schemes for a given source coding problem,- model and assess source coding schemes using the principles of information theory,- analyze given source coding problems, identify and explain the challenges, propose possible solutions, and explain the chosen design.To achive higher grades, participants should also be able to- solve more advanced problems in all areas mentioned above.For single course students: 120 credits and documented proficiency in English B or equivalent.T.M. No
2. Department with academic responsibilityFor more information regarding registration for examination and examination procedures, see "Innsida - Exams"
Data compression.
Learning Outcomes At the end of this module, the student will be able to: 1.
Course educational objectives: 1. Undergraduate Semester level ECE 3040 Minimum Grade of D and (Undergraduate Principles for optimal information transfer across various types of channels.
Ideally, as you are drafting course goals and learning objectives, you are also beginning to develop the assessments for the course. Description of AES (advanced encryption standard) The course learning outcomes and the programme learning outcomes specify the knowledge, understanding, skills, attitudes and values that a student ... Coding Theory, Mechanics and Biomathematics cater to varied interests and . It enables the students to apply these principles and methods in their research tasks. Homework assignments 1.5 ECTS (P/F).
Modelling and analysis of components in a generic communication system.
Determination of channel capacity and its relation to actual communication systems.
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