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T-61.3030 Principles of Neural Computing (5 cp)

TENTATIVE LECTURE SCHEDULE AND LECTURE SLIDES

Date Lecturer Topic Slides
Lecture 1
13.3.
Raivio General information. 1.1-1.7: Introduction info (pdf), pdf
Lecture 2
14.3.
Raivio 2.1-2.5, 2.7-2.8 Learning processes pdf
Lecture 3
20.3.
Raivio 2.9-2.10, 2.12 Learning processes, 3.1-3.3 Single-Layer Perceptrons pdf
Lecture 4
21.3.
Raivio 3.4-3.5, 3.9-3.11: Single-Layer Perceptrons pdf
Lecture 5
27.3.
Raivio 4.1-4.3 Multilayer Perceptrons pdf
Lecture 6
28.3.
Raivio 4.4-4.8 Multilayer Perceptrons pdf
Lecture 7
3.4.
Raivio 4.12-4.14, 4.16 Multilayer Perceptrons pdf
Lecture 8
4.4.
Raivio M. Aksela: Introduction to course assignments, 4.18 Multilayer Perceptrons, 5.1-5.4 Radial-Basis Function Networks pdf
Lecture 9
17.4.
Koskela 5.5-5.11 RBF networks pdf
Lecture 10
18.4.
Koskela 5.13-5.14 RBF networks, 9.1-9.3 Self-Organizing Map pdf
Lecture 11
24.4.
Koskela 9.4-9.6 Self-Organizing Map, Visualization of SOM pdf, pdf
Lecture 12
25.4.
Koskela PicSOM Demo, 9.7-9.8 Learning Vector Quantization pdf

The chapters in the schedule are chapters of the coursebook: S. Haykin: "Neural Networks - a Comprehensive Foundation", 2nd edition, Prentice-Hall, 1998. The slides downloadable from this web page may differ slightly from those presented on the lectures. The figure numbers in the slides refer to the figure numbers of Haykin's book.




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Wednesday, 25-Apr-2007 14:14:53 EEST