An Improved Modeling of Nonlinear Circuits based on Elman Neural Network

Authors

Shao JIE, Key Laboratory of Radar Imaging and Microwave Photonics (Nanjing Univ. Aeronaut. Astronaut.), Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China\\ Key Laboratory of Underwater Acoustic Signal Processing, Ministry of Education, Southeast University, Nanjing, 210096, ChinaFollow
Shu JIAN
Wang LI
Reza Malekian

Author Country (or Countries)

China

Abstract

In this paper, an improved modeling based on Elman neural network was proposed to analyze the nonlinear features of nonlinear circuits with the memory effect. The input vector of the hidden layer in neural network is normalized to enhance the neural network convergence precision. A group of Chebyshev orthogonal basis functions was employed to activate hidden layer neurons. Computer simulation results of the nonlinear power amplifier (PA) have shown that the proposed behavioral modeling not only accurately describes the nonlinear distortions of PAs, but also well depicts memory effect of PAs. And, the proposed approach could be also applied to analyze linear circuits and RF power amplifiers.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.12785/amis/080424

Recommended Citation

JIE, Shao; JIAN, Shu; LI, Wang; and Malekian, Reza (2014) "An Improved Modeling of Nonlinear Circuits based on Elman Neural Network," Applied Mathematics & Information Sciences: Vol. 08: Iss. 4, Article 24.
DOI: http://dx.doi.org/10.12785/amis/080424
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss4/24