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Hyperparameter Optimization of Two-Hidden-Layer Neural Networks for Power Amplifiers Behavioral Modeling Using Genetic Algorithms
IEEE Microwave and Wireless Components Letters ( IF 2.374 ) Pub Date : 2019-11-12 , DOI: 10.1109/lmwc.2019.2950801
Siqi Wang; Morgan Roger; Julien Sarrazin; Caroline Lelandais-Perrault

Neural networks (NNs) are efficient techniques for behavioral modeling of power amplifiers (PAs). This letter proposes a genetic algorithm to determine the optimal hyperparameters of the NN model for a PA. Different activation functions are compared. The necessary number of training epochs is also studied to get an optimal solution with a significantly reduced computational complexity. Experimental measurements on a PA with different signals validate the NN models determined by the proposed method.
更新日期:2020-01-04

 

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