SOM in Hilbert Space

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00333216" target="_blank" >RIV/68407700:21340/19:00333216 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.14311/NNW.2019.29.002" target="_blank" >https://doi.org/10.14311/NNW.2019.29.002</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14311/NNW.2019.29.002" target="_blank" >10.14311/NNW.2019.29.002</a>

Jazyk výsledku
angličtina
Název v původním jazyce
SOM in Hilbert Space
Popis výsledku v původním jazyce
The self organization can be performed in an Euclidean space as usually denned or in any metric space which is generalization of previous one. Both approaches have advantages and disadvantages. A novel method of batch SOM learning is designed to yield from the properties of the Hilbert space. This method is able to operate with finite or infinite dimensional patterns from vector space using only their scalar product. The paper is focused on the formulation of objective function and algorithm for its local minimization in a discrete space of partitions. General methodology is demonstrated on pattern sets from a space of functions.
Název v anglickém jazyce
SOM in Hilbert Space
Popis výsledku anglicky
The self organization can be performed in an Euclidean space as usually denned or in any metric space which is generalization of previous one. Both approaches have advantages and disadvantages. A novel method of batch SOM learning is designed to yield from the properties of the Hilbert space. This method is able to operate with finite or infinite dimensional patterns from vector space using only their scalar product. The paper is focused on the formulation of objective function and algorithm for its local minimization in a discrete space of partitions. General methodology is demonstrated on pattern sets from a space of functions.

Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt
—
Návaznosti
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění
2019
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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