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A new method based on support vector regression (SVR) is proposed to extract the conductivity of the ferromagnetic thin films in this paper. First, the conductivity function with the thickness of the thin films and the reflection coefficients of the network is constructed by SVR based on 3D electromagnetic (EM) simulation data. Then, the reflection coefficients of the network under test are measured...
In this paper, a new method based support vector regression (SVR) is introduced for modeling noise parameters of FETs. Support vector machines (SVMs), which are based on the structural risk minimization (SRM) principle, have powerful generalization ability, and can handle problems with finite samples . By using the proposed method, the effect of the measurement errors can be excellent treated with...
A new method is proposed for electromagnetic parameters (permittivity and permeability) measurement. The microstrip transmission-line is used as measure structure, and supported vector machine (SVM) is introduced to extract actual permittivity and permeability of magnetic materials. Experiment results show that both permittivity and permeability of magnetic materials can be extracted accurately.
We propose a novel method for extracting the electromagnetic parameters (complex permittivity and permeability) of magnetic thin-film materials. The method extracts electromagnetic parameters of the magnetic thin films from effective electromagnetic parameters by using the supported vector machine (SVM). We validated the method in the frequency range of 1-8 GHz. The results show that the errors for...
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