Lectures
The course consists of 13 lectures and 7 exercises. Below is a preliminary lecture plan with problems connected to each lecture.
Solution manual and lecture notes will be distributed on the course Moodle page.
This is a preliminary planing, and it might change along the course:
Cal week | Lecture | Topic | Part in book |
13 | L1 25/3 | Information measures | 3.1-3.2 |
L2 27/3 | Properties of information measures | 3.2-3.3 | |
E1 28/3 | (2.1-.2.4, 2.8-2.11), 3.3-3.10, 3.13-3.15 | ||
14 | L3 1/1 | Optimal source coding and Kraft inequality | 4.1-4.2 |
L4 3/1 | Huffman coding | 4.3 | |
E2 4/1 | 4.1-4.8, 4.11 | ||
15 | L5 8/4 | Information measures for processes | 3.4 |
L6 10/4 | LZ codes | 5.2 | |
E3 11/4 | 3.18-3.21, 5.3, 5.5-5.7 | ||
16 | L7 15/4 | AEP and its consequences | 6.1-6.2 |
E4 17/4 | 6.1-6.3 | ||
17-18 | Eastern and Re-exam period | ||
19 | L8 6/5 | Capacity for DMC | 6.3-6.5 |
L9 8/5 | Channel coding | 7.1-7.2 | |
E5 9/5 | 6.5-6.10, 6.12a, 7.1-7.3 |
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20 | L10 13/5 | Information measures for continuous variables | 8.1-8.2 |
L11 15/5 | Gaussian channel | 9.1-9.3 | |
E6 16/5 | 8.1, 8.2, 8.5-8.10, 9.2-9.4 | ||
21 | L12 20/5 | Parallel Gaussian channels, OFDM and MIMO | 9.2-9.3 |
L13 22/5 | Discrete input Gaussian channel | 10.1-10.4 | |
E7 23/5 |
9.5-9.8, 9.10, 10.1-10.3, 10.5, 10.6, 10.8, (10.7) |
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23 | Exam week (1-8 June) |