Title :
A New Formulation of Dynamic Neural Network for Modeling of Nonlinear RF/Microwave Circuits
Author :
Deo, Makarand ; Xu, Jianjun ; Zhang, Q.J.
Author_Institution :
Dept. of Electronics, Carleton University, 1125 Colonel By Dr., Ottawa, Canada K1S 5B6. mdeo@doe.carleton.ca
Abstract :
In this paper, we propose a new formulation of dynamic neural network (DNN) for modeling of nonlinear RF/microwave devices or circuits in continuous time domain. The proposed model can be trained directly from input-output large-signal data irrespective of internal details of the circuit. The proposed approach maintains the accuracy even in presence of measurement noise in training data. A circuit representation of the proposed model is introduced in order to incorporate it into circuit simulators for high-level design. Examples of dynamic modeling of FET amplifier operating at high frequencies are presented.
Keywords :
Artificial neural networks; Circuit noise; Circuit simulation; Microwave circuits; Microwave devices; Microwave theory and techniques; Neural networks; Radio frequency; Recurrent neural networks; Training data;
Conference_Titel :
Microwave Conference, 2003 33rd European
Conference_Location :
Munich, Germany
Print_ISBN :
1-58053-834-7
DOI :
10.1109/EUMA.2003.340832