Review of Neuro-Space Mapping Modeling for Packaged Transistors

Yan, Shuxia; Zhang, Shuang; Dong, Xu

doi:10.1109/ucmmt49983.2020.9296025

Cited by 1 publication

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The proposed method is applied to the laterally diffused metal-oxide-semiconductor transistor AFT18S230. In this example, the measured AFT18S230 data are the fine model [ 24 ]. The transistor AFT18S290 model in Advanced Design System (ADS), which has a similar performance to the fine model, is chosen as the coarse model.…”

Section: Experiments and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Analytical Separated Neuro-Space Mapping Modeling Method of Power Transistor

Wang

Yan

et al. 2023

Micromachines

View full text Add to dashboard Cite

An analytically separated neuro-space mapping (Neuro-SM) model of power transistors is proposed in this paper. Two separated mapping networks are introduced into the new model to improve the characteristics of the DC and AC, avoiding interference of the internal parameters in neural networks. Novel analytical formulations are derived to develop effective combinations between the mapping networks and the coarse model. In addition, an advanced training approach with simple sensitivity analysis expressions is proposed to accelerate the optimization process. The flexible transformation of terminal signals in the proposed model allows existing models to exceed their current capabilities, addressing accuracy limitations. The modeling experiment for the measurement data of laterally diffused metal-oxide-semiconductor transistors demonstrates that the novel method accurately represents the characteristics of the DC and AC of transistors with a simple structure and efficient training process.

show abstract

Section: Experiments and Discussionmentioning

confidence: 99%

“…Two mapping networks are used to modify the current and voltage signals from the existing device model to the fine data in large-signal simulations [ 23 ]. A small-signal knowledge-based modeling approach, which uses the input and output package modules to improve the small-signal characteristic of transistors, is proposed in [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Analytical Separated Neuro-Space Mapping Modeling Method of Power Transistor

Wang

Yan

et al. 2023

Micromachines

View full text Add to dashboard Cite

show abstract

Review of Neuro-Space Mapping Modeling for Packaged Transistors

Cited by 1 publication

References 9 publications

Analytical Separated Neuro-Space Mapping Modeling Method of Power Transistor

Analytical Separated Neuro-Space Mapping Modeling Method of Power Transistor

Contact Info

Product

Resources

About