TELECOMMUNICATIONS
SEMINAR Tietoliikennetekniikan seminaari
Code: TLTE3090
This time topic is ”Evolutionary algorithms in
Communications and systems”
Credits: 3–10 ECTS (3–10 op)
Prerequisites:
related
subject studies on telecommunication engineering
Learning
Outcomes: the aim of
this course is to introduce research oriented topics in telecommunications and
systems, after completing this course successfully, the student will be able
to seek scientific information and to prepare and give seminar presentations,
moreover, they will be able to demonstrate the principles of the seminar topic
Content: this course has varying content, the
current content is always indicated by the course subtitle presented in the
course website
Study
Materials: 1. depend on
the topic
Teaching
Methods: depending on
the topic
Modes of
Study: attending seminar sessions (most of them), quizzes, preparing scientific report and
giving at least one presentation (some
guidelines in blow)
Languages: english
Grading: 1–5 or failed, or passed/failed (depends
on the topic)
Responsible
Person: Mohammed Elmusrati and Reino Virrankoski
Teacher(s): Mohammed Elmusrati,
Reino Virrankoski
Responsible
Unit: Department
of Computer Science
Additional Information: annual course, website cs.uwasa.fi/courses/tlte3090
Timetable: http://weboodi.uwasa.fi/oodi/
Presentation lecture 3.3.2015
“What are Evolutionary
algorithms”
Presentation lecture 10.3.2015
“More about EAs”
Those who are interested to
learn more about EAs, can read the slides etc. Evolutionary algorithms course
homepage.
A lot of information about EAs
can be found from Wikipedia EA category: https://en.wikipedia.org/wiki/Category:Evolutionary_algorithms
Note, last year we originally
thought that the topic of this seminar would be “MIMO Broadband Communication”,
but we changed it later, but I will make a presentation about how EAs are used
with MIMO systems planning and resource allocation, and will present that in
later in the exercises.
EXERCISES
from 17.3.
You should prepare
presentation, about 20 min from some research paper related to the topic. You
will find suitable research papers with keywords eg.
“evolutionary algorithm” + Telecommunications e.g.
from here:
Most of the pdfs are
downloadable from the University accounts.
Exercise, Week 13, 14:
Matlabise these these java codes (do the same with Matlab)
http://lipas.uwasa.fi/~timan/AUTO3120/
Some programming examples of 1. exercise
FirstGA.java http://lipas.uwasa.fi/~timan/AUTO3120/FirstGA.java
BinaryGA.java other version of binary GA http://lipas.uwasa.fi/~timan/AUTO3120/BinaryGA.java
I will deliver example code later
Some programming
examples of 2. exercise
Some01.java http://lipas.uwasa.fi/~timan/AUTO3120/Some01.java
DE.java http://lipas.uwasa.fi/~timan/AUTO3120/DE.java
DE class source, place in the same directory as
Some01.java
Some programming examples
of 3. exercise
ACOsudo1.java version where numbers are drawn freely
ACOsudo2.java version that forces all lines to have all integers {1, 2, ..., 9} once on and only once all the time
EXERCISE, Week 16: F4104
from 14:30 to 17:00
Test these Matlab codes and try to understand
what they are doing:
Some programming examples
of 4. exercise
GAFIR1.m GA version of FIR designer. There were some problems in class, but b is what we want to find.
DEFIR1.m DE version of FIR designer.
CMA-ES code: http://en.wikipedia.org/wiki/CMA-ES#Example_code_in_MATLAB.2FOctave
BBO-algorithm: http://en.wikipedia.org/wiki/Biogeography-based_optimization#MATLAB
Pareto Front: http://se.mathworks.com/examples/global-optimization/3844-simple-emoo-application-finding-the-pareto-front
EMOO: http://se.mathworks.com/examples/optimization/3852-simple-emoo-problem
Other
evolutionary optimization examples:
https://se.mathworks.com/examples/search/?q=genetic
https://se.mathworks.com/examples/search/?q=particle
Note most of these codes in Mathworks
require Global optimization toolbox which our classroom Matlab
may not have.