Unitary Triangularization of a Nonsymmetric Matrix
Journal of the ACM (JACM)
Quick Finite Element Methods for Electromagnetic Waves with Cdrom
Quick Finite Element Methods for Electromagnetic Waves with Cdrom
Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications
Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications
Soft Computing - A Fusion of Foundations, Methodologies and Applications
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Blur Identification by Multilayer Neural Network Based on Multivalued Neurons
IEEE Transactions on Neural Networks
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A novel identification technique for the extraction of lumped circuit models of general distributed or stray devices is presented. The approach is based on two multi-valued neuron neural networks used in a joined architecture able to extract hidden parameters. The convergence allows the validation of the approximated lumped model and the extraction of the correct values. The inputs of the neural network are the geometrical parameters of a given structure, while the outputs represent the estimation of the lumped circuit parameters. The method uses a frequency response analysis approach in order to elaborate the data to present to the net.