Lectures
The course consists of 13 lectures and 7 exercises. Below is a preliminary lecture plan with problems connected to each lecture.
This is a preliminary planning, and it might change along the course:
Cal week |
Lecture |
Topic |
Part in book |
12 |
L1 22/3 |
Information measures |
3.1 – 3.2 |
L2 24/3 |
Properties of information measures |
3.2 – 3.3 |
|
E1 26/3 |
(2.1 – 2.4, 2.8 – 2.11), 3.3 – 3.10, 3.13 – 3.15 |
||
13 |
L3 29/3 |
Optimal source coding and Kraft inequality |
4.1 – 4.2 |
L4 31/3 |
Huffman coding |
4.3 |
|
E2 31/3 |
4.1 – 4.8, 4.11 |
||
14 – 15 |
Eastern and Re-exam period |
||
16 |
L5 19/4 |
Information measures for processes |
3.4 |
L6 21/4 |
LZ codes |
5.2 |
|
E3 22/4 |
3.18 – 3.21, 5.3, 5.5 – 5.7 |
||
17 |
L7 26/4 |
Two important theorems |
6.1 – 6.2 |
L8 28/4 |
Capacity for DMC |
6.3 – 6.5 |
|
E4 29/4 |
6.1 – 6.3 |
||
18 |
L9 3/5 |
Channel coding |
7.1 – 7.2 |
L10 5/5 |
Information measures for continuous variables |
8.1 – 8.2 |
|
E5 6/5 |
6.5 – 6.10, 6.12a, 7.1 – 7.3 |
||
19 |
L11 10/5 |
Gaussian channel |
9.1 – 9.3 |
E6 12/5 |
8.1, 8.2, 8.5 – 8.10, 9.2 – 9.4 |
||
20 |
L12 17/5 |
Parallel Gaussian channels, OFDM and MIMO |
9.2 – 9.3 |
L13 19/5 |
Discrete input Gaussian channel |
10.1 – 10.4 |
|
E7 20/5 |
9.5 – 9.8, 9.10, 10.1 – 10.3, 10.5, 10.6, 10.8, (10.7) |
||
22 |
Exam week (31/5 – 4/6) |