Aiming at solving the blind estimation problem of dispreading spectrum sequence under low SNR, a spread-spectrum estimation algorithm based subspace tracking is studied in this paper. This method avoids the direct eig...Aiming at solving the blind estimation problem of dispreading spectrum sequence under low SNR, a spread-spectrum estimation algorithm based subspace tracking is studied in this paper. This method avoids the direct eigen decomposition, using the sliding window technique to obtain the code synchronization, then use segmentation subspace tracking method estimate spreading sequence and splice in a certain order to achieve pseudo-code blind estimation. The results show that the algorithm can complete the accurate estimation of PN code sequence in low SNR conditions, reduce the amount of data storage and be easy hardware implementation展开更多
Empirical likelihood(EL) combined with estimating equations(EE) provides a modern semi-parametric alternative to classical estimation techniques such as maximum likelihood estimation(MLE). This paper not only uses clo...Empirical likelihood(EL) combined with estimating equations(EE) provides a modern semi-parametric alternative to classical estimation techniques such as maximum likelihood estimation(MLE). This paper not only uses closed form of conditional expectation and conditional variance of Logistic equation with random perturbation to perform maximum empirical likelihood estimation(MELE) for the model parameters, but also proposes an empirical likelihood ratio statistic(ELRS) for hypotheses concerning the interesting parameter. Monte Carlo simulation results show that MELE and ELRS provide competitive performance to parametric alternatives.展开更多
Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then p...Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.展开更多
文摘Aiming at solving the blind estimation problem of dispreading spectrum sequence under low SNR, a spread-spectrum estimation algorithm based subspace tracking is studied in this paper. This method avoids the direct eigen decomposition, using the sliding window technique to obtain the code synchronization, then use segmentation subspace tracking method estimate spreading sequence and splice in a certain order to achieve pseudo-code blind estimation. The results show that the algorithm can complete the accurate estimation of PN code sequence in low SNR conditions, reduce the amount of data storage and be easy hardware implementation
基金supported by the National Natural Science Foundation of China under Grant No.11101452the Natural Science Foundation Project of CQ CSTC under Grant No.2012jjA00035the National Basic Research Program of China under Grant No.2011CB808000
文摘Empirical likelihood(EL) combined with estimating equations(EE) provides a modern semi-parametric alternative to classical estimation techniques such as maximum likelihood estimation(MLE). This paper not only uses closed form of conditional expectation and conditional variance of Logistic equation with random perturbation to perform maximum empirical likelihood estimation(MELE) for the model parameters, but also proposes an empirical likelihood ratio statistic(ELRS) for hypotheses concerning the interesting parameter. Monte Carlo simulation results show that MELE and ELRS provide competitive performance to parametric alternatives.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51079046, 50909041, 50809025, and 50879024)the National Science and Technology Support Plan (Grant Nos. 2008BAB29B03and 2008BAB29B06)+6 种基金the Special Fund of State Key Laboratory of China (Grant Nos. 2009586012, 2009586912, and 2010585212)the Fundamental Research Funds for the Central Universities (Grant Nos. 2009B08514, 2010B20414, 2010B01414, and 2010B14114)the China Hydropower Engineering Consulting Group Co. Science and Technology Support Pro-ject (Grant No. CHC-KJ-2007-02)Jiangsu Province "333 High-Level Personnel Training Project" (Grant No. 2017-B08037)Graduate Innovation Program of Universities in Jiangsu Province (Grant No. CX09B_ 163Z)Dominant Discipline Construction Program Funded Projects of University in Jiangsu ProvineScience Foundation for the Excellent Youth Scholars of Ministry of Education of China (Grant No. 20070294023)
文摘Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.
