RRAM SPICE modeling with LT spice
This thesis conducts a thorough analysis and explanation based on two theoretical models from Stanford University and Peking University, implements and validates these models using LTspice software. The comparison reveals that building SPICE models through coding is more straightforward and practica...
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Nanyang Technological University
2024
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sg-ntu-dr.10356-1818052024-12-20T15:47:54Z RRAM SPICE modeling with LT spice Guan, Wenjiang Chen Tupei School of Electrical and Electronic Engineering EChenTP@ntu.edu.sg Engineering This thesis conducts a thorough analysis and explanation based on two theoretical models from Stanford University and Peking University, implements and validates these models using LTspice software. The comparison reveals that building SPICE models through coding is more straightforward and practical, while parameter analysis suggests that the Peking University model is more comprehensive, although it is slightly less flexible. Master's degree 2024-12-19T11:16:21Z 2024-12-19T11:16:21Z 2024 Thesis-Master by Coursework Guan, W. (2024). RRAM SPICE modeling with LT spice. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181805 https://hdl.handle.net/10356/181805 en application/pdf Nanyang Technological University |
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This thesis conducts a thorough analysis and explanation based on two theoretical models from Stanford University and Peking University, implements and validates these models using LTspice software. The comparison reveals that building SPICE models through coding is more straightforward and practical, while parameter analysis suggests that the Peking University model is more comprehensive, although it is slightly less flexible. |
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Chen Tupei |
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Chen Tupei Guan, Wenjiang |
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Thesis-Master by Coursework |
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Guan, Wenjiang |
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Guan, Wenjiang |
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RRAM SPICE modeling with LT spice |
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RRAM SPICE modeling with LT spice |
title_full |
RRAM SPICE modeling with LT spice |
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RRAM SPICE modeling with LT spice |
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RRAM SPICE modeling with LT spice |
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rram spice modeling with lt spice |
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Nanyang Technological University |
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2024 |
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https://hdl.handle.net/10356/181805 |
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