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Identificación del sistema basado en el núcleo utilizando funciones de base ortogonales generalizadas y técnicas

Wenfeng Li1, Yang Liu2

  • 1Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150006, China.

ISA transactions
|August 26, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta nuevos métodos para la regularización basada en el núcleo (KRM) en la identificación del sistema. El diseño mejorado del núcleo y la optimización de hiperparámetros meta-heurísticos mejoran el rendimiento de la estimación del modelo.

Área de la Ciencia:

  • Ingeniería de sistemas de control
  • Aprendizaje automático
  • Procesamiento de señales
Palabras clave:
Funciones de base ortogonales generalizadasDiseño del núcleoRegularización basada en el núcleoTécnicas metaheurísticasIdentificación del sistema

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Sus antecedentes:

  • Los métodos de regularización basados en el núcleo (KRM) son fundamentales en la identificación del sistema tanto para los sistemas causales como para los no causales.
  • Los desafíos clave en KRM incluyen el diseño del núcleo y la estimación de hiperparámetros.
  • Los enfoques KRM existentes requieren soluciones sólidas para estos desafíos.