A Neural Network Space Mapping Modeling Method for Large Signal Power Transistors
A technology of power transistors and neural networks, which is applied in the field of microwave circuit and device modeling, can solve problems such as increasing the difficulty of optimization, and achieve the effects of shortening the modeling cycle, simple operation, and simple neural network structure
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[0028] In order to make the object, technical solution and advantages of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
[0029] Such as figure 2 As shown, in a kind of neural network space mapping modeling method for large-signal power transistors of the present invention, the large-signal input sample data is input power, source impedance, load impedance, fundamental frequency, voltage, denoted as [P in ,Z S ,Z L , freq, V gf , V df ] T ; Large signal output sample data are output power, gain, power efficiency, power added power, denoted as [P out , Gain, η, PAE] T .
[0030] build as figure 1 The neural network structure shown. At this time, the model fitted by the measured data in the DC and S-parameter simulation is used as the existing rough model. The mapping network adopts a 3-layer perceptron structure, and the input signal is [i dc_DC , i dc_AC ] T , ...
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