The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology
Author
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-17
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Comprehensive and predictive modeling of submicron devices using the traditional TCAD EDA tools of device simulation has become increasingly perplexing due to a lack of reliable models and difficulties in calibrating available device models.
This paper proposes a new technique to model BCD submicron pMOSFET devices and to predict device behaviors under different bias conditions and different geometry dimensions by using the adaptive neurofuzzy inference system (ANFIS), which combines fuzzy theory and adaptive neuronetworking.
Here, the power of using ANFIS to realize the I-V behaviors is demonstrated in these p-channel MOS transistors.
After a systematic evaluation, it can be found that the predicting results of I-V behaviors of complicated submicron pMOSFETs by ANFIS are compared with the actual diagnostic experiment data, and a good agreement has been obtained.
Furthermore, the error percentage was no greater than 2.5%.
As such, the demonstrated benefits of this new proposed technique include precise prediction and easier implementation.
American Psychological Association (APA)
Chen, Shen-Li. 2015. The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology. Advances in Fuzzy Systems،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1052432
Modern Language Association (MLA)
Chen, Shen-Li. The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology. Advances in Fuzzy Systems No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1052432
American Medical Association (AMA)
Chen, Shen-Li. The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology. Advances in Fuzzy Systems. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1052432
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1052432