Nonlinear multifunctional sensor signal reconstruction based on total least squares

被引：7
|
作者：
Liu, X. [1 ]
Sun, J. W. [1 ]
Liu, D. [1 ]
机构：
[1] Harbin Inst Technol, Dept Automat Measurement & Control, Harbin 150001, Peoples R China
来源：
4TH INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY (ISIST' 2006) | 2006年 / 48卷
关键词：
D O I：
10.1088/1742-6596/48/1/052
中图分类号：
TH7 [仪器、仪表];
学科分类号：
0804 ; 080401 ; 081102 ;
摘要：
The least squares method is often used to estimate the parameters in multi-functional sensor signal reconstruction. If the data has been contaminated, the computational result of the method turns out to be insignificant. Two methods presented in this paper are suitable for different nonlinear conditions, which are based on the combination of the total least squares algorithm with the local linearization strategy and Stone-Weierstrass theorem. The two methods evaluate both the sensor output bias and its input error. The results of emulation and theory analysis indicate that the proposed algorithms are more accurate and reliable for signal reconstruction.
引用
收藏
页码：281 / 286
页数：6
相关论文
共 50 条
  • [1] Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm
    Liu, Xin
    Wei, Guo
    Sun, Jin-wei
    Liu, Dan
    [J]. JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A, 2009, 10 (04): : 497 - 503
  • [2] Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm
    Xin Liu
    Guo Wei
    Jin-wei Sun
    Dan Liu
    [J]. Journal of Zhejiang University-SCIENCE A, 2009, 10 : 497 - 503
  • [3] Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm附视频
    Xin LIU Guo WEI Jinwei SUN Dan LIU Department of Automatic Measurement and Control Harbin Institute of Technology Harbin China
    [J]. Journal of Zhejiang University(Science A:An International Applied Physics & Engineering Journal), 2009, (04) : 497 - 503
  • [4] Nonlinear Multifunctional Sensor Signal Reconstruction Based on Local Least Squares Support Vector Machines
    Liu, Xin
    Sun, Jinwei
    Wei, Guo
    Liu, Dan
    [J]. ICSP: 2008 9TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, VOLS 1-5, PROCEEDINGS, 2008, : 303 - 306
  • [5] ANFIS-Based Signal Reconstruction for Nonlinear Multifunctional Sensor
    Liu J.
    Zhang Y.
    Li C.
    [J]. Journal of The Institution of Engineers (India): Series B, 2019, 100 (05) : 397 - 404
  • [6] Sparse Signal Reconstruction via Orthogonal Least Squares
    Kaur, Arvinder
    Budhiraja, Sumit
    [J]. 2014 FOURTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING AND COMMUNICATION TECHNOLOGIES (ACCT 2014), 2014, : 133 - 137
  • [7] Constrained total least squares for color image reconstruction
    Ng, MK
    Bose, NK
    Koo, J
    [J]. TOTAL LEAST SQUARES AND ERRORS-IN-VARIABLES MODELING: ANALYSIS, ALGORITHMS AND APPLICATIONS, 2002, : 365 - 376
  • [8] Image Reconstruction Algorithm Based on Total Least Squares Target Correction for ECT
    Wang, Lili
    Lv, Hexiang
    Chen, Deyun
    Yang, Hailu
    Li, Mingyu
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2021, 2021
  • [9] PHASE RECONSTRUCTION VIA NONLINEAR LEAST-SQUARES
    DOBSON, DC
    [J]. INVERSE PROBLEMS, 1992, 8 (04) : 541 - 557
  • [10] X-ray radiographs reconstruction based on nonlinear least squares with deconvolution
    Wang, Zhongmiao
    Jing, Yuefeng
    Kang, Xu
    Ding, Tong
    Liu, Jun
    [J]. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2019, 929 : 134 - 141
12345