Anomalous and traditional diffusion modelling in SOM learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00335997" target="_blank" >RIV/68407700:21340/19:00335997 - isvavai.cz</a>

Výsledek na webu

<a href="http://hdl.handle.net/10467/87000" target="_blank" >http://hdl.handle.net/10467/87000</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.24425/acs.2019.131233" target="_blank" >10.24425/acs.2019.131233</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Anomalous and traditional diffusion modelling in SOM learning

Popis výsledku v původním jazyce

The traditional self organizing map (SOM) is learned by Kohonen learning. The main disadvantage of this approach is in epoch based learning when the radius and rate of learning are decreasing functions of epoch index. The aim of study is to demonstrate advantages of diffusive learning in single epoch learning and other cases for both traditional and anomalous diffusion models. We also discuss the differences between traditional and anomalous learning in models and in quality of obtained SOM. The anomalous diffusion model leads to less accurate SOM which is in accordance to biological assumptions of normal diffusive processes in living nervous system. But the traditional Kohonen learning has been overperformed by novel diffusive learning approaches.

Název v anglickém jazyce

Anomalous and traditional diffusion modelling in SOM learning

Popis výsledku anglicky

The traditional self organizing map (SOM) is learned by Kohonen learning. The main disadvantage of this approach is in epoch based learning when the radius and rate of learning are decreasing functions of epoch index. The aim of study is to demonstrate advantages of diffusive learning in single epoch learning and other cases for both traditional and anomalous diffusion models. We also discuss the differences between traditional and anomalous learning in models and in quality of obtained SOM. The anomalous diffusion model leads to less accurate SOM which is in accordance to biological assumptions of normal diffusive processes in living nervous system. But the traditional Kohonen learning has been overperformed by novel diffusive learning approaches.

Druh

J_imp - 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

<a href="/cs/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Výzkumné centrum informatiky</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>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

Název periodika

Archives of Control Sciences

ISSN

2300-2611

e-ISSN

—

Svazek periodika

29

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

19

Strana od-do

699-717

Kód UT WoS článku

000500305900008

EID výsledku v databázi Scopus

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