NON-GAUSSIAN

作品数:103被引量:146H指数:7
导出分析报告
相关领域:电子电信更多>>
相关作者:尹建君刘阳张厚道严以京徐瑞雪更多>>
相关机构:复旦大学东南大学中国科学技术大学同济大学更多>>
相关期刊:更多>>
相关基金:国家自然科学基金国家重点基础研究发展计划国防科技技术预先研究基金安徽省自然科学基金更多>>
-

检索结果分析

结果分析中...
选择条件:
  • 学科=自动化与计算机技术—检测技术与自动化装置x
条 记 录,以下是1-4
视图:
排序:
Sequential fusion estimation for multisensor systems with non-Gaussian noises被引量:2
《Science China(Information Sciences)》2020年第12期149-161,共13页Liping YAN Chenying DI Q.M.Jonathan WU Yuanqing XIA 
supported by Beijing Natural Science Foundation(Grant No.4202071)。
The sequential fusion estimation for multisensor systems disturbed by non-Gaussian but heavytailed noises is studied in this paper.Based on multivariate t-distribution and the approximate t-filter,the sequential fusio...
关键词:state estimation sequential fusion non-Gaussian disturbance heavy-tailed noise multivariate t-distribution 
Multi-objective PID control for non-Gaussian stochastic distribution system based on two-step intelligent models被引量:3
《Science in China(Series F)》2009年第10期1754-1765,共12页YI Yang ZHANG TianPing GUO Lei 
Supported by the National Natural Science Foundation of China (Grant Nos. 60774013, 60874045, 60904030)
A new method for controlling the shape of the conditional output probability density function (PDF) for general nonlinear dynamic stochastic systems is proposed based on B-spline neural network (NN) model and T-S ...
关键词:probability density function non-Gaussian stochastic systems PID controller B-spline NN L1 performance index T-S fuzzy model 
Statistic PID Tracking Control for Non-Gaussian Stochastic Systems Based on T-S Fuzzy Model被引量:3
《International Journal of Automation and computing》2009年第1期81-87,共7页Yang Yi Hong Shen Lei Gu 
supported by National Natural Science Foundationof China (No. 60472065, No. 60774013).
A new robust proportional-integral-derivative (PID) tracking control framework is considered for stochastic systems with non-Gaussian variable based on B-spline neural network approximation and T-S fuzzy model ident...
关键词:Non-Gaussian systems probability density function statistic tracking control T-S fuzzy model proportional-integralderivative control. 
Batch process monitoring based on multilevel ICA-PCA被引量:3
《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2008年第8期1061-1069,共9页Zhi-qiang GE Zhi-huan SONG 
Project (No. 60774067) supported by the National Natural ScienceFoundation of China
In this paper, we describe a new batch process monitoring method based on multilevel independent component analysis and principal component analysis (MLICA-PCA). Unlike the conventional multi-way principal component a...
关键词:MULTILEVEL Independent component analysis (ICA) Principal component analysis (PCA) Batch process monitoring NON-GAUSSIAN 
检索报告 对象比较 聚类工具 使用帮助 返回顶部