Items where Author is "Bártfai, Gusztáv"

Up a level
Export as [feed] Atom [feed] RSS 1.0 [feed] RSS 2.0
Group by: Date | Item Type | No Grouping
Number of items: 8.
DateAuthor/TitleDocument Type
2007Argyros, A. and Bártfai, Gusztáv and Eitzinger, Ch. and Kemény, Zsolt and Csáji, Balázs Csanád and Kék, László and Lourakis, M. and Reisner, W. and Sandrisser, W. and Sarmis, T. and Umgeher, G. and Viharos, Zsolt János
Smart sensor based vision system for automated processes
Book Section
2007Argyros, A. and Bártfai, Gusztáv and Eitzinger, Ch. and Kemény, Zsolt and Csáji, Balázs Csanád and Kék, László and Lourakis, M. and Reisner, W. and Sandrisser, W. and Sarmis, T. and Umgeher, G. and Viharos, Zsolt János
Smart sensor based vision system for automated processes
Article
2002Brendel, M. and Roska, Tamás and Bártfai, Gusztáv
Gradient computation of continuous-time cellular neural/nonlinear networks with linear templates via the CNN universal machine
Article
1999Bártfai, Gusztáv
Combination of adaptive resonance theory (ART) and cellular neural network (CNN) chips into a high-speed pattern recognition system. ( Research report of the Analogical and Neural Computing Laboratory, DNS-1-1999.)
Book
1999Földesy, Péter and Kék, László and Zarándy, Ákos and Roska, Tamás and Bártfai, Gusztáv
Fault-tolerant design of analogic CNN templates and algorithms - Part I: The binary output case
Article
1999Bártfai, Gusztáv
Towards implementation of biologically inspired autonomous and adaptive information processing systems
Thesis
1998Földesy, Péter and Kék, László and Roska, Tamás and Zarándy, Ákos and Bártfai, Gusztáv
Fault tolerant CNN template design and optimatization based on chip measurements
Conference or Workshop Item
1998Földesy, Péter and Kék, László and Zarándy, Ákos and Roska, Tamás and Bártfai, Gusztáv
Fault tolerant design of analogic CNN templates and algorithms. Part I: The binary output case.(Research report of the Analogical and Neural Computing Laboratory, DNS-3-1998.)
Book
This list was generated on Thu Nov 21 03:13:59 2024 CET.