Machine learning technique based extremely broadband small‐signal behavioral model for InP DHBTs-Reference-Cited by-同舟云学术

Machine learning technique based extremely broadband small‐signal behavioral model for InP DHBTs

Published:2020-04-04 Issue:7 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:

Cai Jialin¹²^ORCID,Liu Jun¹,King Justin³,Sun Lingling¹

Affiliation:

1. Key Laboratory of RF Circuit and SystemMinistry of Education, Hangzhou Dianzi University Hangzhou China

2. Key Lab Foundation of Science and Technology on Monolithic Integrated Circuits and Modules Laboratory Jiangsu China

3. RF & Microwave Research GroupTrinity College Dublin Dublin Ireland

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

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

Link

Reference41 articles.

4. Large‐signal HBT model with improved collector transit time formulation for GaAs and InP technologies;Iwamoto M;IEEE MTT‐Symp Digest,2003

5. A custom III‐V heterojunction bipolar transistor model;Nedeljkovic S;Microw J,2009

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