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Multidimensional signal-noise neural network model

机译:多维信噪神经网络模型

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Signal and noise behaviours of microwave transistors are modelled through the neural network approach for the whole operating ranges including frequency, bias and configuration types. 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 multiple bias and configuration. The concurrent modelling procedure does not require the solving of device physics equations repeatedly during optimisation, and by this type of modelling the signal (S) and noise (N) parameters can be predicted not only at a single operation frequency around the chosen bias condition for a configuration, but at the same time for the whole operation frequency band for the same operating conditions, with good agreement compared to the measurements.
机译:微波晶体管的信号和噪声行为通过神经网络方法对整个工作范围进行建模,包括频率,偏置和配置类型。在此,该设备由一个黑匣子建模,该黑匣子的小信号和噪声参数是通过神经网络基于两个参数对多个偏置和配置的拟合来评估的。并行建模过程不需要在优化过程中反复求解设备物理方程,通过这种建模,不仅可以在选定的偏置条件附近的单个工作频率下预测信号(S)和噪声(N)参数。一种配置,但同时在相同的工作条件下针对整个工作频段,与测量值相比具有良好的一致性。

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