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.