Red neuronal estructurada en el espacio de estados como modelo de caja gris
- Jesús M. Zamarreño 1
- Alejandro Merino 2
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1
Universidad de Valladolid
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2
Universidad de Burgos
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- Jose Luis Calvo Rolle (coord.)
- Jose Luis Casteleiro Roca (coord.)
- María Isabel Fernández Ibáñez (coord.)
- Óscar Fontenla Romero (coord.)
- Esteban Jove Pérez (coord.)
- Alberto José Leira Rejas (coord.)
- José Antonio López Vázquez (coord.)
- Vanesa Loureiro Vázquez (coord.)
- María Carmen Meizoso López (coord.)
- Francisco Javier Pérez Castelo (coord.)
- Andrés José Piñón Pazos (coord.)
- Héctor Quintián Pardo (coord.)
- Juan Manuel Rivas Rodríguez (coord.)
- Benigno Rodríguez Gómez (coord.)
- Rafael Alejandro Vega Vega (coord.)
Publisher: Servizo de Publicacións ; Universidade da Coruña
ISBN: 978-84-9749-716-9
Year of publication: 2019
Pages: 639-646
Congress: Jornadas de Automática (40. 2019. Ferrol)
Type: Conference paper
Abstract
State space neural networks (ssNN) has demonstrated very good properties when modelling dynamic systems in the past. In this paper we propose an evolution of the neural network when information about the inner structure of the system is available in the form any kind of model. With this information, a grey-box model is obtained that represents in a better way the system to be modelled. This model has been named structured state space neural network (sssNN). A simulated example is presented as a case study
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