National Repository of Grey Literature 599 records found  beginprevious580 - 589next  jump to record: Search took 0.01 seconds. 
Character recognition system
HANZLÍK, Ondřej
"The thesis proposes a system for recognition of printed text (OCR), which uses neural network for recognizing letters. The neural network is implemented using the program RapidMiner. To control the neural network is using the processes created by program RapidMiner. These processes are run directly from a Java application. RapidMiner is implemented into the java application and using its libraries is started directly from java application." directly from a Java application. RapidMiner is implemented into the java application and using its libraries is started directly from java application."
Neuronové Sítě jako semiparametrická metoda oceňování opcí
Baruník, Jozef ; Baruníková, M.
We study the ability of artificial neural networks to price the European style call and put options on the S&P 500 index.
Analysis of Decay Processes Separation
Jiřina, Marcel ; Hakl, František
Fulltext: content.csg - Download fulltextPDF
Plný tet: v1035-08 - Download fulltextPDF
Vybrané rozšířené příspěvky z mezinárodní konference CSIT 2006 (Počítačové vědy a informační technologie) - speciální číslo časopisu NNW
Húsek, Dušan ; Snášel, V. ; El-Qawasmeth, E.
Editors present extended versions of the best papers from the 4th International Multiconference on Computer Science and Information Technology 2006 (CSIT 2006 ) in special issue of NNW journal. Selected were the most influential papers on artificial intelligence and knowledge engineering, including biologically motivated methods.(Neural Network World 16, 4 (2006) 275-368.)
Binární faktorová analýza založená na neuronových sítích jako nástroj pro shlukování velkých datových souborů
Frolov, A. A. ; Húsek, Dušan ; Snášel, Václav ; Řezanková, H. ; Polyakov, P.Y.
The feature space transformation is a widely used method for data compression. Due to this transformation the original patterns are mapped into the space of features or factors of reduced dimensionality. In this paper we demonstrate that Hebbian learning in Hopfield-like neural network is a natural procedure for binary factorization. This paper is dedicated to estimation of the size of attraction basins around factors. Two global spurious attractors are shown to prevent convergence of the network activity to the factors invalidating any procedure of their search. These global attractors can be completely deleted from network dynamics by introducing a single inhibitory neuron with bi-directional Hebbian synapses. Due to additional inhibition, the size of attraction basins around factors becomes the same as around the stored patterns in usual Hopfield network.

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