Ntecs.de

8. May, 2008

by Michael Neumann

After working very hard during the last couple of weeks on my study thesis, I finished the last chapters today. In short what I did was to implement a performance efficient spiking neural net simulator from scratch in C++, including interfaces for Octave/Matlab (oh, how ugly can an interface be!) and Ruby.

The time writing reminded me at the time when I was writing the Ruby Developers Guide book back in 2001. At the beginning, you need to force yourself to get some sentences written. But after a while they flow more and more fluent out of your mouth (hands).

Ah, should I mention that I wrote my study thesis in English? I did it mainly to get a wider audience, but also because sometimes it is easier to describe technical aspects in English than it is in German, because a lot of words in computer sciene are already in English. But I have still problems with commats and English grammar :)

Autonomic Grid Computing

11. July, 2007

13. July, 2007

Presentation

Study

by Michael Neumann

I put this presentation I gave a few years ago online again. In German!

Mobilkommunikation

18. July, 2004

Study

by Michael Neumann

When: Summer 2004
Lecturers: Prof. M. Zitterbart, K. Weniger
URL: www.tm.uka.de/lehre/aktSS/vorlesungen/V_MK.html

Neuronal Nets

18. July, 2004

Study

by Michael Neumann

When: Summer 2004
Lecturer: Prof. A. Waibel
URL: not-yet

Classifiers

supervised, non-supervised
parametric, non-parametric (parametric means that for each class a probability-distribution is known)
linear, non-linear
Bayes Classifier
Gaussian Classifier (parametric Bayes-classifier which uses a Gaussian distribution)
Parzen-Window (used in non-parametric classifiers; calculates the probability for a given sample)
K-nearest Neighbor (non-linear, non-parametric)
Perceptron (linear, non-parametric)

Timetable Summer 2004

18. July, 2004

Study

by Michael Neumann

| Time | Monday | Tuesday | Wednesday | Thursday | Friday | | 8:00 - 9:30 | | | RechStru [HMU] | | {Kosmo}[Kosmo] [HS B] | | 9:45 - 11:15 | KomDat-Ü [Gaede] | | | ZellAlgo [MM HS] | KomDat [Gaede] | | 11:30 - 13:00 | | MobiKom [Redtenbach] | KogSys [HMO] | KomDat [Gaede] | | | 14:00 - 15:30 | KogSys [HMU] | NeuroNet [236 50.36]| EchZSys [HMU] | RechStru [HMU] | | | 15:45 - 17:15 | | EchZSys [HMU] | NetzSich [MM HS]| | |

Legend

EchZSys:	Echtzeit Systeme (Real-time Systems)
RechStru:	Rechner Strukturen (Computer Structures)
KogSys:	Kognitive Systeme (Cognitive Systems/Artifical Intelligence)
KomDat:	Kommunikation und Datenhaltung (Communication and Datakeeping)
NeuroNet:	Neuronale Netze (Neural Networks)
MobiKom:	Mobilkommunikation (Mobile Communication)
NetzSich:	Netzwerksicherheit: Architektur und Protokolle (Network Security: Architecture and Protocols)
{Kosmo}[Kosmo]:	Einführung in die Kosmologie (Introduction into Cosmology)
ZellAlgo:	Algorithmen in Zellulärautomaten (Algorithms in Cellular automatons)