The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology
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...
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2015/824524 |
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| author | Shen-Li Chen |
| author_facet | Shen-Li Chen |
| author_sort | Shen-Li Chen |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-7220b141d19a4b8396ccb7aac52e4cf0 |
| institution | OA Journals |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-7220b141d19a4b8396ccb7aac52e4cf02025-08-20T02:06:23ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2015-01-01201510.1155/2015/824524824524The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based MethodologyShen-Li Chen0Department of Electronic Engineering, National United University, 2 Lien-Da Road, Miaoli City 36003, TaiwanComprehensive 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.http://dx.doi.org/10.1155/2015/824524 |
| spellingShingle | Shen-Li Chen The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology Advances in Fuzzy Systems |
| title | The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology |
| title_full | The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology |
| title_fullStr | The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology |
| title_full_unstemmed | The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology |
| title_short | The I-V Characteristic Prediction of BCD LV pMOSFET Devices Based on an ANFIS-Based Methodology |
| title_sort | i v characteristic prediction of bcd lv pmosfet devices based on an anfis based methodology |
| url | http://dx.doi.org/10.1155/2015/824524 |
| work_keys_str_mv | AT shenlichen theivcharacteristicpredictionofbcdlvpmosfetdevicesbasedonananfisbasedmethodology AT shenlichen ivcharacteristicpredictionofbcdlvpmosfetdevicesbasedonananfisbasedmethodology |