Training guidelines for neural networks to estimate stability regions

Enrique D. Ferreira, Bruce H. Krogh

Producción científica: Contribución a una revistaArtículo de la conferenciarevisión exhaustiva

Resumen

This paper presents new results on the use of neural networks to estimate stability regions for autonomous nonlinear systems. In contrast to model-based analytical methods, this approach uses empirical data from the system to train the neural network. A method is developed to generate confidence intervals for the regions identified by the trained neural network. The neural network results are compared with estimates obtained by previously proposed methods for a standard two-dimensional example.

Idioma originalInglés
Páginas (desde-hasta)2829-2833
Número de páginas5
PublicaciónProceedings of the American Control Conference
Volumen4
EstadoPublicada - 1999
Publicado de forma externa
EventoProceedings of the 1999 American Control Conference (99ACC) - San Diego, CA, USA
Duración: 2 jun. 19994 jun. 1999

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