| Dates: | ||
| Wednesday | 10:15 - 12:00 am | OH 14 / R. 304 |
| First Lecture: | Wednesday, 13-OCT-2010 | |
Tutorials: Dr. Mohammad Abam, LS 2 (web pages)
Each Wednesday: group 1 at 12:00h, group 2 at 16:00h.
Instruction Language: English.
For a German version of this web page please click the 'Deutsch' button at the top right corner.
Examinations:
| Program | Type | Requirements | |
|---|---|---|---|
| Informatics, | Diplom | : Leistungsnachweis | -> must pass tutorial |
| Informatics, | Diplom | : Fachprüfung | -> oral examination (30 min) |
| Informatics, | Bachelor | : Module | -> oral examination (30 min) |
| Automation & Robotics, | Master | : Module | -> oral examination (30 min) |
Description:
Typically, Computational Intelligence is used as an umbrella term for the fields of
artificial neural nets (ANN), fuzzy systems (FS) and evolutionary computation (EC).
This course offers a thorough introduction into all three fields.
Foundations of ANN: McCulloch-Pitts nets, perceptrons, Hopfield nets, supervised and unsupervised learning, backpropagation.
Foundations of FS: Fuzzy sets, fuzzy numbers, fuzzy logic, fuzzy reasoning.
Foundations of EC: Algorithmic basics, parameterization, analysis methods, limits of deployment.
Students should get an overview about the different aspects of Computational Intelligence. They should be familiar with the essential elements in all three fields (ANN, FS, EC) and able to deploy and adapt these methods for real applications. Moreover, they should be able to assess when to deploy these methods and when not.
Foundations of ANN: McCulloch-Pitts nets, perceptrons, Hopfield nets, supervised and unsupervised learning, backpropagation.
Foundations of FS: Fuzzy sets, fuzzy numbers, fuzzy logic, fuzzy reasoning.
Foundations of EC: Algorithmic basics, parameterization, analysis methods, limits of deployment.
Students should get an overview about the different aspects of Computational Intelligence. They should be familiar with the essential elements in all three fields (ANN, FS, EC) and able to deploy and adapt these methods for real applications. Moreover, they should be able to assess when to deploy these methods and when not.
Slides:
| 13.10.10 | Artificial Neural Networks I |  |
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| 20.10.10 | Artificial Neural Networks II | |
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| 27.10.10 | Artificial Neural Networks III | |
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| 03.11.10 | Artificial Neural Networks IV | |
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| 10.11.10 | Fuzzy Systems I | |
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| 17.11.10 | Fuzzy Systems II | |
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| 24.11.10 | Fuzzy Systems III | |
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| 01.12.10 | Fuzzy Systems IV | |
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| 08.12.10 | cancelled | ||||
| 15.12.10 | Fuzzy Systems V | (to be delivered) | |||
| 05.01.11 | Evolutionary Algorithms I | |
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| 12.01.11 | Evolutionary Algorithms II (Part A) | |
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| Evolutionary Algorithms II (Part B) | |
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| 19.01.11 | Evolutionary Algorithms III | ||||
| 26.01.11 | Evolutionary Algorithms IV | ||||
| 02.02.11 | Swarm Intelligence | |
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Literature:
- Raul Rojas: Neural Networks - A Systematic Introduction. Spinger 1996. Available online.
- G.J. Klir and B. Yuan: Fuzzy Sets and Fuzzy Logic. Prentice Hall 1995.