Full Text:   <2091>

CLC number: TN98

On-line Access: 

Received: 2008-04-14

Revision Accepted: 2008-10-10

Crosschecked: 2009-03-13

Cited: 3

Clicked: 3207

Citations:  Bibtex RefMan EndNote GB/T7714

-   Go to

Article info.
1. Reference List
Open peer comments

Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.4 P.497~503

http://doi.org/10.1631/jzus.A0820282


Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm


Author(s):  Xin LIU, Guo WEI, Jin-wei SUN, Dan LIU

Affiliation(s):  Department of Automatic Measurement and Control, Harbin Institute of Technology, Harbin 150001, China

Corresponding email(s):   xinliu@hit.edu.cn

Key Words:  Least squares support vector machine, Total least squares, Multifunctional sensor, Signal reconstruction


Xin LIU, Guo WEI, Jin-wei SUN, Dan LIU. Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm[J]. Journal of Zhejiang University Science A, 2009, 10(4): 497~503.

@article{title="Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm",
author="Xin LIU, Guo WEI, Jin-wei SUN, Dan LIU",
journal="Journal of Zhejiang University Science A",
volume="10",
number="4",
pages="497~503",
year="2009",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0820282"
}

%0 Journal Article
%T Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm
%A Xin LIU
%A Guo WEI
%A Jin-wei SUN
%A Dan LIU
%J Journal of Zhejiang University SCIENCE A
%V 10
%N 4
%P 497~503
%@ 1673-565X
%D 2009
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820282

TY - JOUR
T1 - Nonlinear multifunctional sensor signal reconstruction based on least squares support vector machines and total least squares algorithm
A1 - Xin LIU
A1 - Guo WEI
A1 - Jin-wei SUN
A1 - Dan LIU
J0 - Journal of Zhejiang University Science A
VL - 10
IS - 4
SP - 497
EP - 503
%@ 1673-565X
Y1 - 2009
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A0820282


Abstract: 
least squares support vector machines (LS-SVMs) are modified support vector machines (SVMs) that involve equality constraints and work with a least squares cost function, which simplifies the optimization procedure. In this paper, a novel training algorithm based on total least squares (TLS) for an LS-SVM is presented and applied to multifunctional sensor signal reconstruction. For three different nonlinearities of a multifunctional sensor model, the reconstruction accuracies of input signals are 0.001 36%, 0.031 84% and 0.504 80%, respectively. The experimental results demonstrate the higher reliability and accuracy of the proposed method for multifunctional sensor signal reconstruction than the original LS-SVM training algorithm, and verify the feasibility and stability of the proposed method.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1] Bates, D.M., Watts, D.G., 1980. Relative curvature measures of nonlinearity. J. Royal Stat. Soc. Ser. B, 42:1-25.

[2] Box, M.J., 1971. Bias in nonlinear estimation. J. Royal Stat. Soc. Ser. B, 33:171-201.

[3] Cortes, C., Vapnik, V., 1995. Support-vector networks. Machine Learning, 20(3):273-297.

[4] Flammini, A., Marioli, D., Taroni, A., 1999. Application of an optimal look-up table to sensor data processing. IEEE Trans. Instrum. Meas., 48(4):813-816.

[5] Liu, D., Sun, J.W., Wei, G., Liu, X., 2007. Application of moving least squares to multi-sensors data reconstruction. Acta Autom. Sin., 33(8):823-828 (in Chinese).

[6] Moreira, M.F.P., Ferreira, M.D., Freire, J.T., 2006. Evaluation of pseudo-homogeneous models for heat transfer in packed beds with gas flow and gas-liquid cocurrent downflow and upflow. Chem. Eng. Sci., 61(6):2056-2068.

[7] Rahman, M.D., Yu, K.B., 1987. Total least squares approach for frequency estimation using linear prediction. IEEE Trans. Acoust., Speech, Signal Processing, 35(10):1440-1454.

[8] Ribeiro, J.A., Oliveira, D.T., Passos, M.L., Barrozo, M.A.S., 2005. The use of nonlinearity measures to discriminate the equilibrium moisture equations for Bixa orellana seeds. J. Food Eng., 66(1):63-68.

[9] Smola, A.J., Scholkopf, B., 2004. A tutorial on support vector regression. Stat. Comput., 14(3):199-222.

[10] Sun, J.W., Shida, K., 2002. Multilayer sensing and aggregation approach to environmental perception with one multifunctional sensor. IEEE Sensors J., 2(2):62-72.

[11] Sun, J.W., Liu, X., Sun, S.H., 2004. TLS algorithm-based study on multi-functional sensor data reconstruction. Acta Electron. Sin., 32(3):391-394 (in Chinese).

[12] Suykens, J.A.K., Vandewalle, J., 1999. Least squares support vector machine classifiers. Neural Processing Lett., 9(3):293-300.

[13] Suykens, J.A.K., Brabanter, J., Lukas, L., Vandewalle, J., 2002. Weighted least squares support vector machines: robustness and sparse approximation. Neurocomputing, 48(1-4):85-105.

[14] Vapnik, V., 1998. The Nature of Statistical Learning Theory. Springer-Verlag, New York.

[15] Vapnik, V., 1999. An overview of statistical learning theory. IEEE Trans. Neural Networks, 10(5):988-999.

[16] Yuji, J., Shida, K., 2000. A new multifunctional tactile sensing technique by selective data processing. IEEE Trans. Instrum. Meas., 49(5):1091-1094.

[17] Zhang, H.Y., Huang, J.D., Fan, W.L., 1995. Total least square method and its application to parameter estimation. Acta Autom. Sin., 21(1):40-47 (in Chinese).

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - Journal of Zhejiang University-SCIENCE