Method for modeling synchronous double-frequency power amplifier based on real number time delay neural network
A technology of power amplifiers and neural network models, applied in biological neural network models, neural learning methods, instruments, etc., can solve the problems of fewer dual-frequency power amplifiers, increase the nonlinear effect of components, and realize inconvenience, and achieve a learning method Flexible, easy to implement, and less complex effects
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[0040] refer to figure 1 , showing the first embodiment of the modeling method of the synchronous dual-frequency power amplifier based on the neural network model of the present invention, comprising the following steps:
[0041] Step 101, establishing a real number delay neural network of a synchronous dual-frequency power amplifier.
[0042] refer to figure 2, which shows the established real delay neural network model of synchronous dual-frequency power amplifier. The neural network in this model has a three-layer feed-forward structure, which are input layer, hidden layer and output layer respectively. The reverse rebroadcast algorithm is used to Approximating the nonlinear characteristics of synchronous dual-band power amplifiers. The real delay structure is used to describe the memory effect of a synchronous dual-band power amplifier.
[0043] Assuming that the baseband input signal of the synchronous dual-band power amplifier is used by I in1 (n), Q in1 (n), I in...
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