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Echo State Networks (ESN) are a type of Recurrent Neural Network that yields promising results in representing time series and nonlinear dynamic systems. Although they are equipped with a very efficient training procedure, Reservoir Computing strateg
Externí odkaz:
http://arxiv.org/abs/2211.17179
Autor:
Antonelo, Eric Aislan, Camponogara, Eduardo, Seman, Laio Oriel, Jordanou, Jean Panaioti, de Souza, Eduardo Rehbein, Hübner, Jomi Fred
Publikováno v:
In Neurocomputing 28 April 2024 579
Autor:
de Amorim, Juan F., Jordanou, Jean Panaioti, Moreno, Ubirajara F., Normey Rico, Júlio Elias, Vieira, Bruno Ferreira
Publikováno v:
In IFAC PapersOnLine 2024 58(14):241-246
Publikováno v:
In Neurocomputing 1 September 2023 548
Akademický článek
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Autor:
Jordanou, Jean Panaioti1 (AUTHOR) jeanpanaioti@gmail.com, Antonelo, Eric Aislan1 (AUTHOR), Camponogara, Eduardo1 (AUTHOR)
Publikováno v:
IEEE Transactions on Neural Networks & Learning Systems. Jun2022, Vol. 33 Issue 6, p2615-2629. 15p.
Autor:
Jordanou, Jean Panaioti, Antonelo, Eric Aislan, Camponogara, Eduardo, S. de Aguiar, Marco Aurelio
Publikováno v:
Brazilian Symposium on Intelligent Automation, Porto Alegre 1-4 October 2017 (pp. 924-931). (2017).
Echo State Networks (ESN) are dynamical learning models composed of two parts: a recurrent network (reservoir) with fixed weights and a linear adaptive readout output layer. The output layer’s weights are learned for the ESN to reproduce temporal p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2658::e0c83fa879cb55ab50f9e307e8284ff8
http://orbilu.uni.lu/handle/10993/32852
http://orbilu.uni.lu/handle/10993/32852