Neural Computers and Their Applications
Code  Completion  Credits  Range  Language 

01NSAP  ZK  4  3+0  Czech 
 Garant předmětu:
 Lecturer:
 Tutor:
 Supervisor:
 Department of Mathematics
 Synopsis:

Introduction into the theory of artificial neural networks, some important kinds of neural networks, threshold vectors analysis of binary nets, neural networks evaluation of Boolean functions, neural networks from the point of view of function approximation, neural networks from the point of view of probability theory, numerical properties of learning algorithms.
 Requirements:
 Syllabus of lectures:

Introduction to neural networks, basic models, analysis of binary neural networks, approximations possibilities of neural networks, VapnikChervonenkis dimension of NN, learning theory and neural networks, numerical aspects of learning algorithms, applications of probabilistic theory in neural networks, fuzzy sets approach to neural networks.
 Syllabus of tutorials:
 Study Objective:

Make the students acquainted with theoretical and mathematical fundamentals of important kinds of neural networks.
 Study materials:

[1] H. White. Artificial Neural Networks: Approximation and Learning Theory. Blackwell Publishers, Cambridge, 1992 [2] Vwani Roychowdhury, KaiYeung Siu, Alon Orlitsky. Theoretical Advances in Neural Computation and Learning. Kluwer Academic Publishers, 1994
 Note:
 Further information:
 No timetable has been prepared for this course
 The course is a part of the following study plans:

 Matematické inženýrství (elective course)