Artificial Neural Networks

This lecture presents standard algorithms and new developments of Artificial Neural Networks, their functioning, application domains, and connections to more conventional mathematical methods. Examples show the potential and limitations of the methods. Supervised as well as unsupervised learning methods are introduced.



Course type
Winter Term 2014/2015


Takes place every week on Friday from 12:15 to 14:00 in room HZO 100.
First appointment is on 10.10.2014
Takes place every week on Wednesday from 14:00 to 15:00 in room HZO 100.
First appointment is on 15.10.2014

Certificate: Upon successful completion of the exercises (1 HPW)


  • Lecture notes by C. Goerick
  • C. M. Bishop, Neural Networks for Pattern Recognition, 1995 Clarendon Press, Oxford.

The Institut für Neuroinformatik (INI) is a central research unit of the Ruhr-Universität Bochum. We aim to understand the fundamental principles through which organisms generate behavior and cognition while linked to their environments through sensory systems and while acting in those environments through effector systems. Inspired by our insights into such natural cognitive systems, we seek new solutions to problems of information processing in artificial cognitive systems. We draw from a variety of disciplines that include experimental approaches from psychology and neurophysiology as well as theoretical approaches from physics, mathematics, electrical engineering and applied computer science, in particular machine learning, artificial intelligence, and computer vision.

Universitätsstr. 150, Building NB, Room 3/32
D-44801 Bochum, Germany

Tel: (+49) 234 32-28967
Fax: (+49) 234 32-14210