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...
| Главные авторы: | , , |
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| Формат: | Статья |
| Язык: | English |
| Опубликовано: |
Springer
2024-03-01
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| Серии: | Industrial Artificial Intelligence |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1007/s44244-024-00017-7 |