The aim of this work is to present a novel technique for the identification of lumped circuit models of general distributed apparatus and devices. It is based on the use of a double modified complex value neural network. The method is not oriented to a unique class of electromagnetic systems, but it gives a procedure for the complete validation of the approximated lumped model and the extraction of the electrical parameter values. The inputs of the system are the geometrical (and/or manufacturing) parameters of the considered structure, while the outputs are the lumped circuit parameters. The method follows the Frequency Response Analysis (FRA) approach for elaborating the data presented to the network.
Analog system modeling based on a double modified complex valued neural network / A. Luchetta; S. Manetti; M. C. Piccirilli. - ELETTRONICO. - (2013), pp. 1-8. (Intervento presentato al convegno The 2013 International Joint Conference on Neural Networks (IJCNN) tenutosi a Dallas, TX nel 4-9 Aug. 2013) [10.1109/IJCNN.2013.6707136].
Analog system modeling based on a double modified complex valued neural network
LUCHETTA, ANTONIO;MANETTI, STEFANO;PICCIRILLI, MARIA CRISTINA
2013
Abstract
The aim of this work is to present a novel technique for the identification of lumped circuit models of general distributed apparatus and devices. It is based on the use of a double modified complex value neural network. The method is not oriented to a unique class of electromagnetic systems, but it gives a procedure for the complete validation of the approximated lumped model and the extraction of the electrical parameter values. The inputs of the system are the geometrical (and/or manufacturing) parameters of the considered structure, while the outputs are the lumped circuit parameters. The method follows the Frequency Response Analysis (FRA) approach for elaborating the data presented to the network.File | Dimensione | Formato | |
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