- identify information, coding and communication problems
- explain coding and compression methods and information limits
- apply accepted knowledge to real systems analysis
- analyze complex information and communication systems
- explain phenomens in different areas of science
- estimate performances of different information and communication systems
- apply techniques of entropy and error correcting codes
Forms of Teaching
Lectures are held in three hour units.Independent assignments
Students solve problems, not mandatory for everyone.Laboratory
Mandatory for all students, each subgroup solves one problem.
|Type||Threshold||Percent of Grade||Threshold||Percent of Grade|
|Mid Term Exam: Written||10 %||50 %||0 %|
|Final Exam: Written||10 %||50 %|
|Exam: Written||40 %||100 %|
Although laboratory exercises does not contribute to a total number of points won on this course, their accomplishment is necessary requirement.
Week by Week Schedule
- Information theory history and importance; Symbol, message, information, communication.
- Discrete communication system, probabilistic view and information measures.
- Entropy, noiseless coding theorem; Mutual information.
- Information sources .
- Types of codes; Optimal code; Entropy coding.
- Entropy coding.
- Entropy coding; Lossy coding.
- Midterm exam.
- Error detecting and correcting codes, block codes.
- Hamming distance, code equivalence, perfect codes.
- Binary linear block codes, generating matrix, parity check matrix, syndrom.
- Types of binary linear block codes.
- Convolutional and turbo coding.
- Channel capacity, noisy-channel coding theorem.
- Final exam.