Small signal behavioral modeling technique of GaN high electron mobility transistor using artificial neural network: An accurate, fast, and reliable approach-Reference-Cited by-同舟云学术

Small signal behavioral modeling technique of GaN high electron mobility transistor using artificial neural network: An accurate, fast, and reliable approach

Published:2019-12-28 Issue:4 Volume:30 Page:
ISSN:1096-4290
Container-title:International Journal of RF and Microwave Computer-Aided Engineering
language:en
Short-container-title:Int J RF Microw Comput Aided Eng

Author:

Khusro Ahmad¹^ORCID,Husain Saddam¹,Hashmi Mohammad S.²³,Ansari Abdul Quaiyum¹

Affiliation:

1. Department of Electrical Engineering Jamia Millia Islamia (A Central University) New Delhi India

2. Department of Electrical and Computer Engineering Nazarbayev University Astana Kazakhstan

3. Department of Electronics and Communication Engineering Indraprastha Institute of Information Technology‐Delhi (IIIT‐Delhi) New Delhi India

Funder

Ministry of Electronics and Information technology

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Computer Science Applications

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mmce.22112

Reference47 articles.

1. History of GaN: high‐power RF gallium nitride (GaN) from infancy to manufacturable process and beyond;Runton DW;IEEE Microw Wirel Compon Lett,2013

2. Transistor Modeling: Robust Small-Signal Equivalent Circuit Extraction in Various HEMT Technologies

3. A survey of Gallium Nitride HEMT for RF and high power applications

4. AlGaN/GaN HEMTs on SiC and Si substrates: A review from the small-signal-modeling's perspective

5. A 67 GHz GaN Voltage-Controlled Oscillator MMIC With High Output Power

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