A BSIM SOI Model Parameter Extraction Method for SOI MOSFETs Based on PSO

ZHANG Guo-he; ZHENG Xue; CHEN Ke-bin

Chinese

您当前的位置：

首页 >

文章列表页 >

A BSIM SOI Model Parameter Extraction Method for SOI MOSFETs Based on PSO

更新时间：2026-09-04

- A BSIM SOI Model Parameter Extraction Method for SOI MOSFETs Based on PSO
- Vol. 30, Issue 1, Pages: 90-93(2013)
- 作者机构：
  
  西安交通大学电信学院,陕西,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013
- 稿件说明：
移动端阅览
张国和, 郑雪, 陈克斌. 基于粒子群优化算法的BSIM SOI模型参数提取[J]. 微电子学与计算机, 2013, 30(1): 90-93.

ZHANG Guo-he, ZHENG Xue, CHEN Ke-bin. A BSIM SOI Model Parameter Extraction Method for SOI MOSFETs Based on PSO[J]. 2013, 30(1): 90-93.
张国和, 郑雪, 陈克斌. 基于粒子群优化算法的BSIM SOI模型参数提取[J]. 微电子学与计算机, 2013, 30(1): 90-93. DOI：

ZHANG Guo-he, ZHENG Xue, CHEN Ke-bin. A BSIM SOI Model Parameter Extraction Method for SOI MOSFETs Based on PSO[J]. 2013, 30(1): 90-93. DOI：

摘要

本文给出一种基于粒子群优化算法的BSIM SOI MOSFETs模型参数提取方法.该方法采用全局优化策略

计算简单

对初值依赖性低

使用浮点数编码方法

避免了数码转换时所出现的误差.与遗传算法参数提取相比

粒子群优化算法无需进行交叉、变异等操作

容易理解

易于实现

且收敛速度更快.对用该方法得到的参数值代入器件模型进行了计算

计算结果与测试结果吻合很好.本方法亦可用作对其他种类的MOSFETs进行全局参数提取.

Abstract

A method to extract model parameters based on PSO(Particle Swarm Optimization) algorithm is presented for BSIM SOI(Silicon on Insulator) devices in this paper.Using global optimization

this method has simple calculation and has low dependence on initial value.The use of float-encoding in this method avoids the error of digital transfer.Compared with parameter extraction method based on Genetic Algorithm

this method does not require crossover and mutation operations.And it can be easily understood and implement

and has high speed as well.Computation is very simple using this method and it does not require an in-depth understanding of the model equation or a lot of experience with parameter extraction.Using parameters found by this method

the simulation results are matched well with the measurement data.This method also can be applied to other kind of MOSFETs(Metal-Oxide-Semiconductor Field Effect Transistor) for global parameter extraction.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Steganography model guided by attention mechanism and improved dense convolution

Research on the design of blockchain-based AI-generated content traceability framework

Implementation and verification of a dual-chain power gating strategy for low power design

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Simulation on the DC characteristics of double heterojunction p-GaN HEMT with AlN/GaN hybrid buffer layer

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰