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A learning algorithm concept for updating look-up tables for automotive applications

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A learning algorithm concept for updating look-up tables for automotive applications

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Guardiola García, C.; Plá Moreno, B.; Blanco Rodriguez, D.; Cabrera López, P. (2013). A learning algorithm concept for updating look-up tables for automotive applications. Mathematical and Computer Modelling. 57(7-8):1979-1989. doi:10.1016/j.mcm.2011.02.001

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/50901

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Title: A learning algorithm concept for updating look-up tables for automotive applications
Author:
UPV Unit: Universitat Politècnica de València. Instituto Universitario CMT-Motores Térmicos - Institut Universitari CMT-Motors Tèrmics
Universitat Politècnica de València. Departamento de Máquinas y Motores Térmicos - Departament de Màquines i Motors Tèrmics
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Abstract:
Look-up tables are commonly used in the automotive field for handling operating point variations. However, constant maps cannot cope with systems variations and ageing. Methods, such as Kalman filter or Extended Kalman ...[+]
Subjects: Kalman filter , Adaptive models , Maps , Look-up table , Automotive , Sensor
Copyrigths: Reserva de todos los derechos
Source:
Mathematical and Computer Modelling. (issn: 0895-7177 )
DOI: 10.1016/j.mcm.2011.02.001
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.mcm.2012.02.001
Type: Artículo

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