Universal approximation property of stochastic configuration networks for time series

Abstract For the purpose of processing sequential data, such as time series, and addressing the challenge of manually tuning the architecture of traditional recurrent neural networks (RNNs), this paper introduces a novel approach-the Recurrent Stochastic Configuration Network (RSCN). This network is...

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Detalhes bibliográficos
Main Authors: Jin-Xi Zhang, Hangyi Zhao, Xuefeng Zhang
Formato: Artigo
Idioma:English
Publicado em: Springer 2024-03-01
Colecção:Industrial Artificial Intelligence
Assuntos:
Acesso em linha:https://doi.org/10.1007/s44244-024-00017-7