By Topic

Recognition of events detected during nuclear research experiments

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
M. Jirina ; Inst. of Comput. Sci., Czechoslovak Acad. of Sci., Prague, Czech Republic

The principle of nuclear experiments is described. During an experiment, two kinds of events may arise-so called “electrons” and “jets”. The target is to separate these two kinds of events as much as possible. For useful data (electrons), the “accept” signal is generated. Only these data are transferred for more detailed analysis. Each event has the form of a matrix of integers. These data are preprocessed and then classified by a neural classifier. There is need for rather high speed processing as these data arrive at a frequency of 100 kHz. A neural net with a layered architecture and step nonlinearity is described for such applications. Results showing the effectiveness of this neural net approach are presented and methods of hardware implementation are discussed

Published in:

Industrial Electronics, 1996. ISIE '96., Proceedings of the IEEE International Symposium on  (Volume:1 )

Date of Conference:

17-20 Jun 1996