Abstract
Small-signal and noise behaviour of an active microwave device is modeled through the neural network approach for multiple bias/configurations.Here ,the device is modelled by a black box whose small signal and noise parameters are evaluated through a neural network,based upon the fitting of both of these parameters for the multiplebias or configuration. The concurrent modelling procedure does not require to solve device pbysics equations repeatedly during optimization. Compared to the existing device modelling techniques, the proposed approach has the capability to make bighdimensional models for higbly nonlinear devices.
Highlights
the device is modelled by a black box whose small signal and noise parameters are evaluated through a neural network
I 995-MIT-43(2), pp. 293-298. [3).F.GONE~,F.GORGEN and H.TORP1,"Signal-noise neural network model for active microwave devices", IEE Proc,Circuits Devices and Syst.,Vo\.l43,No, 1"February 1996, pp, 18,
Summary
J YlldlZ Technical University, Electronics &Communication Eng. Dept,80670 fviASlAKISTANBULITURJ(jYE. The stages of the \Wrk can be ordered as follows: (i) Establish a novel neural network of feedforward type with a single hidden layer, (ii) using back-propagation and nonlinear types of activation functions ,train the network for both the signal-noise behaviours over the operational bandwidth for multiple bias and multiple configuration of any type of microwave transistor. (iii) Establish performance measure of the model, (iv) Predict the small-signal and noise behaviours at any operation frequency around any bias condition of any type of configuration using the neural network which has already been trained to make functional approximations of the device nonlinear characteristics in the vicinities of the chosen bias points.
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