Echo State Queueing Networks: A Combination of Reservoir Computing and Random Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F17%3A00311786" target="_blank" >RIV/68407700:21230/17:00311786 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.cambridge.org/core/journals/probability-in-the-engineering-and-informational-sciences/article/echo-state-queueing-networks-a-combination-of-reservoir-computing-and-random-neural-networks/B61D5741A5AD03BC3B6433BA139940D4" target="_blank" >https://www.cambridge.org/core/journals/probability-in-the-engineering-and-informational-sciences/article/echo-state-queueing-networks-a-combination-of-reservoir-computing-and-random-neural-networks/B61D5741A5AD03BC3B6433BA139940D4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1017/S0269964817000110" target="_blank" >10.1017/S0269964817000110</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Echo State Queueing Networks: A Combination of Reservoir Computing and Random Neural Networks

Popis výsledku v původním jazyce

This paper deals with two ideas appeared during the last developing phase in Artificial Intelligence: Reservoir Computing (RC) and Random Neural Networks. Both have been very successful in many applications. We propose a new model belonging to the first class, taking the structure of the second for its dynamics. The new model is called Echo State Queuing Network. The paper positions the model in the global Machine Learning area, and provides examples of its use and performances. We show on largely used benchmarks that it is a very accurate tool, and we illustrate how it compares with standard RC models.

Název v anglickém jazyce

Echo State Queueing Networks: A Combination of Reservoir Computing and Random Neural Networks

Popis výsledku anglicky

This paper deals with two ideas appeared during the last developing phase in Artificial Intelligence: Reservoir Computing (RC) and Random Neural Networks. Both have been very successful in many applications. We propose a new model belonging to the first class, taking the structure of the second for its dynamics. The new model is called Echo State Queuing Network. The paper positions the model in the global Machine Learning area, and provides examples of its use and performances. We show on largely used benchmarks that it is a very accurate tool, and we illustrate how it compares with standard RC models.

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

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Probability in the Engineering and Informational Sciences

ISSN

0269-9648

e-ISSN

1469-8951

Svazek periodika

31

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

20

Strana od-do

457-476

Kód UT WoS článku

000411729100006

EID výsledku v databázi Scopus

2-s2.0-85019205684