Title :
Neural networks for nonlinear modeling of microwave Schottky diodes
Author :
Liang, Anhui ; Xu, Yanfeng ; Jia, Shouqing ; Sun, Guoquan
Author_Institution :
Nat. Key Lab. of Electron. Meas. Technol., Qingdao
Abstract :
Neural-network computational modules have gained recognition as an unconventional and useful tool for RF and microwave modeling and design. In this paper, we present a study of modeling of microwave Schottky diode by using the neural network techniques, the diode´s nonlinear power characteristics is analyzing based on neural network model. The results of computer simulation show that the output of the neural network model output is well accordance with the output of real nonlinear commercial harmonic-balance software.
Keywords :
Schottky diodes; electronic engineering computing; microwave diodes; neural nets; semiconductor device models; microwave Schottky diodes; neural network; nonlinear modeling; Artificial neural networks; Biological neural networks; Computer networks; Microwave circuits; Microwave devices; Microwave technology; Neural networks; Radio frequency; Schottky diodes; Signal design; Large signal; Schottky diodes; neural networks; nonlinear modeling;
Conference_Titel :
Microwave and Millimeter Wave Technology, 2008. ICMMT 2008. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-1879-4
Electronic_ISBN :
978-1-4244-1880-0
DOI :
10.1109/ICMMT.2008.4540453