HEMT Transistor Noise modeling using generalized radial basis function

In this paper, one important architecture of neural networks named a generalized radial basis function (GRBF) is applied in order to model HEMT transistor noise parameters dependence on bias conditions such as DC drain-to-source voltage, DC drain-to-source current, frequency and S-parameters that can accurately predict transistor noise parameters in a wide frequency ranges for all bias points from the operating range including transistor S-parameters.