An Improved Image Reconstruction Algorithm of Electrical Capacitance Tomography Based on RBF Neural Network

ZHANG Li-feng; HU Hai-tao; CHEN De-yun

Chinese

您当前的位置：

首页 >

文章列表页 >

An Improved Image Reconstruction Algorithm of Electrical Capacitance Tomography Based on RBF Neural Network

更新时间：2026-07-10

- An Improved Image Reconstruction Algorithm of Electrical Capacitance Tomography Based on RBF Neural Network
- Vol. 13, Issue 6, Pages: 5-8(2008)
- 作者机构：
  
  [1]哈尔滨理工大学计算机科学与技术学院,黑龙江,哈尔滨,150080
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2008
- 稿件说明：
移动端阅览
ZHANG Li-feng, HU Hai-tao, CHEN De-yun. An Improved Image Reconstruction Algorithm of Electrical Capacitance Tomography Based on RBF Neural Network[J]. 2008, 13(6): 5-8.
DOI：

ZHANG Li-feng, HU Hai-tao, CHEN De-yun. An Improved Image Reconstruction Algorithm of Electrical Capacitance Tomography Based on RBF Neural Network[J]. 2008, 13(6): 5-8. DOI：

摘要

RBF神经网络图像重建算法在电容层析成像系统中应用广泛，它较好地克服了ECT系统的软场特性、强非线性和不适定性，其成像时间和成像精确度比其他算法都有很多改善．本文从有限元场域剖分、数据归一化和神经网络输入层角度对该算法进行了相关改进．仿真实验结果证明，改进后的算法有着更好的成像时间和成像精确度．

Abstract

RBF neural network has higher reconstruction quality and reconstruction speed than other image reconstruction algorithms when used in image reconstruction. It overcame well soft field characteristic

strong nonlinear and ill - posedness of electrical capacitance tomography. This paper improved the algorithm from finite element plotting pattern

data normalization and input layers. The simulation results show the improved method is effective and accurate for image reconstruction.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Context-Aware Feature Augmentation Method for Person Re-Identification

Cooperative Optimal Scheduling Strategy of Agent Reinforcement Learning based on Source-load Characteristic Analysis

Performance Study of Cavitation Unit with Internalbore at Variable Rotational Speeds

Health Prediction of Electric Meter Calibration Lines by Combining Memory Network and Attention

Hölder Continuity of Solutions for a Class of Elliptic Equations

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