A low-order nonlinear amplifier model with distributed delay terms

Date

2014-01-01

Author

YÜZER, AHMET HAYRETTİN
Demir, Şimşek

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

220
views

0
downloads

In this paper, a novel behavioral modeling technique for the characterization of memory effects of amplifiers is proposed. This characterization utilizes asymmetric intermodulation distortion (IMD)components, which are the result of a 2-tone excitation of a nonlinear amplifier. These asymmetric IMD components are represented basically by a power series, where each term in the series has its own time delay term. These time delay terms successfully justify the presence of asymmetry in the intermodulation components, which leads to the prediction of amplitude-to-amplitude and amplitude-to-phase distortions. The parameters of the model are extracted using 2-tone measurements. A 100-W peak power amplifier is examined. Model predictions are verified by the measurement results of a 4-tone stimulus. The proposed model can also be used in time domain analysis with arbitrary excitation.

Subject Keywords

Electrical and Electronic Engineering, General Computer Science

URI

https://hdl.handle.net/11511/34462

Journal

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES

DOI

https://doi.org/10.3906/elk-1208-25

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Fast and accurate semiautomatic haptic segmentation of brain tumor in 3D MRI images Latifi-Navid, Masoud; Bilen, Murat; Konukseven, Erhan İlhan; Doğan, Musa; Altun, Adnan (The Scientific and Technological Research Council of Turkey, 2016-01-01) In this study, a novel virtual reality-based interactive method combined with the application of a graphical processing unit (GPU) is proposed for the semiautomatic segmentation of 3D magnetic resonance imaging (MRI) of the brain. The key point of our approach is to use haptic force feedback guidance for the selection of seed points in a bounded volume with similar intensity and gradient. For the automatic determination of a bounded volume of segmentation in real time, parallel computation on the GPU is use...
A Cascadable Random Neural Network Chip with Reconfigurable Topology Badaroglu, Mustafa; Halıcı, Uğur; Aybay, Isik; Cerkez, Cuneyt (Oxford University Press (OUP), 2010-03-01) A digital integrated circuit (IC) is realized using the random neural network (RNN) model introduced by Gelenbe. The RNN IC employs both configurable routing and random signaling. In this paper we present the networking/routing aspects as well as the performance results of an RNN network implemented by the RNN IC. In the RNN model, each neuron accumulates arriving signals and can fire if its potential at a given instant of time is strictly positive. Firing occurs at random, the intervals between successive ...
A novel CEM technique for modeling electromagnetic scattering from metasurfaces ÖZGÜN, ÖZLEM; Mittra, Raj; Kuzuoğlu, Mustafa (Wiley, 2020-03-01) This paper presents a novel computational electromagnetics (CEM) technique, which hybridizes the periodic finite element method (FEM) with the method of moments (MoM), for efficient numerical modeling of electromagnetic scattering from metasurfaces consisting of truncated periodic or locally varying quasi-periodic array of structures. Based on the quasi-periodic nature of metasurfaces, the periodic FEM is employed to generate high-level macro basis functions (MBFs). Following that, a reduced MoM matrix is f...
Visual Result Prediction in Electromagnetic Simulations Using Machine Learning Karaosmanoglu, Bariscan; Ergül, Özgür Salih (Institute of Electrical and Electronics Engineers (IEEE), 2019-11-01) In this letter, we present a novel approach based on using convolutional neural networks (CNNs) to visually predict solutions of electromagnetic problems. CNN models are constructed and trained such that images of surface currents obtained at the early stages of an iterative solution can be used to predict images of the final (converged) solution. Numerical experiments demonstrate that the predicted images contain significantly better visual details than the corresponding input images. The developed approac...
State-space identification of switching linear discrete time-periodic systems with known scheduling signals Uyanik, Ismail; Hamzacebi, Hasan; Ankaralı, Mustafa Mert (The Scientific and Technological Research Council of Turkey, 2019-01-01) In this paper, we propose a novel frequency domain state-space identification method for switching linear discrete time-periodic (LDTP) systems with known scheduling signals. The state-space identification problem of linear time-invariant (LTI) systems has been widely studied both in the time and frequency domains. Indeed, there have been several studies that also concentrated on state-space identification of both continuous and discrete linear time-periodic (LTP) systems. The focus in this study is the fam...

Citation Formats

A. H. YÜZER and Ş. Demir, “A low-order nonlinear amplifier model with distributed delay terms,” TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, pp. 1007–1016, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34462.