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Course description 1998/99

2D1430 Artificial Neural Networks and Neural Physiology

KTH credits

6
Lectures
40
Level
D
Tutorials
-
Grading, KTH
U, 3, 4, 5
Lab work
24
Compulsory for
-


Elective for
D, E, F
Periods
3-4
Language
Swedish
Web info
www.nada.kth.se/kurser/kth/2D1430
Coordinator

Anders Lansner, +46 - 8 - 790 6210, ala@sans.kth.se

Abstract

Advanced course in computer science focusing on neural networks and neural physiology.

Goals

The goal of the course is to give the students

so that they will be able to Syllabus

How the neurons are constructed and function. Synaptic transmission and plasticity. The functional organization of the neural system. Modeling and simulation of real neural networks. The most well known ANN-architectures and algorithms for learning. Methods for unsupervised learning. Principles for neural network representation. Hardware architectures for neural computations (neural chips and neural computers). Examples of technical applications of ANN in areas like pattern recognition, combinatoric optimization, diagnosis, and robotics.

Prerequisites

The mandatory courses in mathematics, numerical analysis and computer science or the equivalent.

Follow-up

Please discuss with the instructor.

Examination

A written examination (TEN1; 5 cr.).
Laboratory assignments (LAB1; 1 cr.).

Course material

Reading list available at the department. In 97/98: H. Reichert: Introduction to neurobiology, Georg Thieme Verlag, 1992 and S. Haykin: Neural networks - A comprehensive foundation, Macmillan College Publ, Co, NY, 1994.

Link to course description 1997/98

^ Up to the home page of the course (in Swedish)


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