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Analysis and modelling of CMOS Gm-C filters through machine learning.

Authors :
Ivanova, Malinka
Pasheva, Vesela
Popivanov, Nedyu
Venkov, George
Source :
AIP Conference Proceedings; 2020, Vol. 2333 Issue 1, p1-11, 11p
Publication Year :
2020

Abstract

Utilization of machine learning in electronics and in computer-aided design is in progress, giving an opportunity the electronic circuits to be studied in a new way that also contributes to automation of some engineering tasks. In this paper, a novel methodology for analysis and design of Gm-C filters is presented. It is based on applying classification machine learning algorithm Random Forest on theoretically gathered data sets and on published scientific results. The tree-based algorithm is chosen, because of its capability not only to identify the correct class for every training sample and to point out the decision, but also to give explanation related to this decision and to outline a set of rules. The proposed methodology is verified through creation of several data models. Gm-C filters are chosen for exploration because of their extensive usage in computer and communication systems, medical devices and sensors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2333
Issue :
1
Database :
Complementary Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
149168284
Full Text :
https://doi.org/10.1063/5.0041743