Abstract
AbstractA radial‐basis function neural network (RBFNN) approach is proposed for predicting the nonlinear behaviors of gallium nitride (GaN) Doherty amplifier. Sampled input and output data from a designed GaN Doherty amplifier were used to train and test the proposed RBFNN model. Comparison of amplitude modulation to amplitude modulation (AM/AM), amplitude modulation to phase modulation (AM/PM), gain, power added efficiency (PAE) and output power (Pout) curves among the RBFNN method, circuit simulation and measurement are given. The results indicate that the proposed RBFNN model can reproduce the nonlinear characteristics of the designed GaN Doherty amplifier accurately. © 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 307–309, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24924
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