Cognitive Processes

Lecturer:

Tutor:

Supervisor:

Department of Cybernetics

Synopsis:

The aim of the subject is to provide students with knowledge of basic functions of brain, receptors´ information processing, memory and learning. Further significance of learning and its realisation in technical systems is discussed. Special attention is focused on selected methods of machine learning and softcomputing.

Requirements:

Syllabus of lectures:

1.Brain and methods for its investigation

2.Cognitive functions

3.Memory and learning

4.Machine learning

5.Machine learning

6.Machine learning

7.Neural networks

8.Neural networks

9.Neural networks

10.Neural networks

11.Evolutionary algorithms

12.Evolutionary algorithms

13.Evolutionary algorithms

14.Evolutionary algorithms

Syllabus of tutorials:

1.Brain and functions of receptors

2.Processing of visual and acoustic information

3.Types of memory, ways of learning

4.Machine learning - overview of methods, examples

5.Machine learning - examples

6.Machine learning - examples

7.Neural networks - overview of methods, examples

8.Neural networks - examples

9.Neural networks - examples

10.Neural networks - examples

11.Evolutionary algorithms - formulation of the problem

12.Evolutionary algorithms - examples

13.Evolutionary algorithms - examples

14.Evolutionary algorithms - examples

Study Objective:

Study materials:

(1) Ito, M.: The Cerebellum and Neuronal Control. Raven Press, New York 1984

(2) Posner, M.I. (ed.): Foundations of Cognitive Science. MIT Press, 1996

(3) Churchland, P.M.: A Neurocomputational Perspective: The Nature of Mind and the Structure of Science. MIT Press, 1992

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: