𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Noise wave modeling of microwave transistors based on neural networks

✍ Scribed by Vera Marković; Olivera Pronić; Zlatica Marinković

Publisher
John Wiley and Sons
Year
2004
Tongue
English
Weight
96 KB
Volume
41
Category
Article
ISSN
0895-2477

No coin nor oath required. For personal study only.

✦ Synopsis

Abstract

The noise modeling of microwave FETs based on the noise‐wave representation of a transistor‐intrinsic circuit is considered. Frequency‐dependent noise‐wave temperatures are introduced as empirical model parameters and modeled using neural networks. In this way, online optimization in a circuit simulator is shifted to offline training of neural networks. An example of transistor‐noise modeling for one specified component is shown. © 2004 Wiley Periodicals, Inc. Microwave Opt Technol Lett 41: 294–297, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.20120

📜 SIMILAR VOLUMES

Artificial neural network applications i
Artificial neural network applications in improved noise wave modeling of microwave FETs
✍ Zlatica D. Marinković; Olivera Pronić-Rančić; Vera Marković 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 489 KB

## Abstract An application of artificial neural networks (ANNs) for accuracy improving of the microwave FETs (MESFET/HEMT, dual‐gate MESFET) noise modeling is presented in this paper. The proposed model is based on a basic transistor noise wave model, whose noise wave temperatures are assumed to be

Noise modeling of heterojunction bipolar
Noise modeling of heterojunction bipolar transistors using neural network approach
✍ V. Marković; S. Prasad; A. Stoǐć 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 141 KB

## Abstract The advantages of heterojunction bipolar transistors (HBTs) make them very promising for modern RF communication systems and therefore their noise performance becomes an important issue as well. A procedure for HBT noise modeling based on the neural network approach is presented in this

Bias-dependent scalable modeling of micr
Bias-dependent scalable modeling of microwave FETs based on artificial neural networks
✍ Zlatica D. Marinković; Olivera R. Pronić; Vera V. Marković 📂 Article 📅 2006 🏛 John Wiley and Sons 🌐 English ⚖ 299 KB 👁 1 views

A simple and efficient procedure for modeling of scattering and noise parameters for a class of microwave transistors manufactured in the same technology is presented in this article. It is based on multilayer perceptron artificial neural networks (ANN), whose inputs are device gate width, biases, a

Applications of knowledge-based artifici
Applications of knowledge-based artificial neural network modeling to microwave components
✍ P. M. Watson; K. C. Gupta; R. L. Mahajan 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 197 KB 👁 2 views

This paper expands upon reported methods for utilizing prior knowledge for reducing complexity of input-output relationships that an ANN must learn. Previously, two simple methods, difference method and prior knowledge input method, were demonstrated for new model developments. This paper utilizes k

Modeling power and intermodulation behav
Modeling power and intermodulation behavior of microwave transistors with unified small-signal/large-signal neural network models
✍ F. Giannini; G. Leuzzi; G. Orengo; P. Colantonio 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 260 KB

This article presents a detailed procedure to learn a nonlinear model and its derivatives to as many orders as desired with multilayer perceptron (MLP) neural networks. A modular neural network modeling a nonlinear function and its derivatives is introduced. The method has been used for the extracti