Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex enviro...Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex environment.In this paper,a robust localization algorithm based on Gaussian mixture model and fitting polynomial is proposed to solve the problem of NLOS error.Firstly,fitting polynomials are used to predict the measured values.The residuals of predicted and measured values are clustered by Gaussian mixture model(GMM).The LOS probability and NLOS probability are calculated according to the clustering centers.The measured values are filtered by Kalman filter(KF),variable parameter unscented Kalman filter(VPUKF)and variable parameter particle filter(VPPF)in turn.The distance value processed by KF and VPUKF and the distance value processed by KF,VPUKF and VPPF are combined according to probability.Finally,the maximum likelihood method is used to calculate the position coordinate estimation.Through simulation comparison,the proposed algorithm has better positioning accuracy than several comparison algorithms in this paper.And it shows strong robustness in strong NLOS environment.展开更多
In order to extract the information of 662-keV 137Cs spectra from the overlapping peaks with 583-keV 208Tl,609-keV 214Bi,the overlapping peaks are measured by in-situ γ-ray spectrometer using a NaI(Tl) detector.The s...In order to extract the information of 662-keV 137Cs spectra from the overlapping peaks with 583-keV 208Tl,609-keV 214Bi,the overlapping peaks are measured by in-situ γ-ray spectrometer using a NaI(Tl) detector.The spectral model is optimized by the Gaussian fitting algorithm,and the optimized fitting indexes for fitting/original value are from 0.96 to 0.99.Gaussian fitting verified by experiment is feasible for γ-ray spectrum analysis.The full energy peak of 137Cs is extracted correctly from the overlapping peaks,it is important for in-situ γ-ray spectrometer to estimate contamination of 137Cs in radiated environment and nuclear accident.展开更多
The optical frequency comb has been widely used in precision measurement. In this study, a multi-peak fitting approach is first proposed to fit the two-photon transition spectrum which overlaps with the neighboring tr...The optical frequency comb has been widely used in precision measurement. In this study, a multi-peak fitting approach is first proposed to fit the two-photon transition spectrum which overlaps with the neighboring transition in Rb-87. The multi-peak fitting approach is used to eliminate the frequency shift affected by the neighboring transition. With locking the carrier envelope offset frequency at 1/4 repetition frequency, the transition frequency is measured to be 770569132739.9 +/- 5.8 kHz, which agrees well with the previous result recommended by Comite International des Poids et Mesures.展开更多
湿法炼锌浸出液中存在多金属组分,如Zn(Ⅱ)和Co(Ⅱ),针对重叠峰分离提出一种基于类Gaussian分布的线性扫描极谱重叠峰分离方法。通过分析线性扫描极谱曲线的特性构造类Gaussian分布作为待分离重叠峰子峰的模型,并利用多分辨率小波分解...湿法炼锌浸出液中存在多金属组分,如Zn(Ⅱ)和Co(Ⅱ),针对重叠峰分离提出一种基于类Gaussian分布的线性扫描极谱重叠峰分离方法。通过分析线性扫描极谱曲线的特性构造类Gaussian分布作为待分离重叠峰子峰的模型,并利用多分辨率小波分解确定各子峰波峰和波谷位置,基于该模型及确定值对重叠峰及其导数峰进行非线性加权最小二乘(nonlinear weighted least squares,NWLS)拟合,根据重构参数将重叠峰分离为独立的子峰,实现该类重叠峰的分离。该类重叠峰分离的结果表明:多分辨率小波分解的分辨误差小于1%,NWLS拟合的分离精度高于96%,本方法可以有效分离Zn(Ⅱ)和Co(Ⅱ)产生的极谱重叠峰。展开更多
In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in paral...In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in parallel. The search space was projected into multiple subspaces and searched by sub-populations. Also, the whole space was exploited by the other population which exchanges information with the sub-populations. In order to make the evolutionary course efficient, multivariate Gaussian model and Gaussian mixture model were used in both populations separately to estimate the distribution of individuals and reproduce new generations. For the surrogate model, Gaussian process was combined with the algorithm which predicted variance of the predictions. The results on six benchmark functions show that the new algorithm performs better than other surrogate-model based algorithms and the computation complexity is only 10% of the original estimation of distribution algorithm.展开更多
基金supported by the National Natural Science Foundation of China under Grant No.62273083 and No.61973069Natural Science Foundation of Hebei Province under Grant No.F2020501012。
文摘Wireless sensor network(WSN)positioning has a good effect on indoor positioning,so it has received extensive attention in the field of positioning.Non-line-of sight(NLOS)is a primary challenge in indoor complex environment.In this paper,a robust localization algorithm based on Gaussian mixture model and fitting polynomial is proposed to solve the problem of NLOS error.Firstly,fitting polynomials are used to predict the measured values.The residuals of predicted and measured values are clustered by Gaussian mixture model(GMM).The LOS probability and NLOS probability are calculated according to the clustering centers.The measured values are filtered by Kalman filter(KF),variable parameter unscented Kalman filter(VPUKF)and variable parameter particle filter(VPPF)in turn.The distance value processed by KF and VPUKF and the distance value processed by KF,VPUKF and VPPF are combined according to probability.Finally,the maximum likelihood method is used to calculate the position coordinate estimation.Through simulation comparison,the proposed algorithm has better positioning accuracy than several comparison algorithms in this paper.And it shows strong robustness in strong NLOS environment.
基金Supported by National Natural Science Foundation of China(No.40274023 and No.40674067)
文摘In order to extract the information of 662-keV 137Cs spectra from the overlapping peaks with 583-keV 208Tl,609-keV 214Bi,the overlapping peaks are measured by in-situ γ-ray spectrometer using a NaI(Tl) detector.The spectral model is optimized by the Gaussian fitting algorithm,and the optimized fitting indexes for fitting/original value are from 0.96 to 0.99.Gaussian fitting verified by experiment is feasible for γ-ray spectrum analysis.The full energy peak of 137Cs is extracted correctly from the overlapping peaks,it is important for in-situ γ-ray spectrometer to estimate contamination of 137Cs in radiated environment and nuclear accident.
基金Supported by the National Natural Science Foundation of China under Grant Nos 91336103,10934010 and 61078026
文摘The optical frequency comb has been widely used in precision measurement. In this study, a multi-peak fitting approach is first proposed to fit the two-photon transition spectrum which overlaps with the neighboring transition in Rb-87. The multi-peak fitting approach is used to eliminate the frequency shift affected by the neighboring transition. With locking the carrier envelope offset frequency at 1/4 repetition frequency, the transition frequency is measured to be 770569132739.9 +/- 5.8 kHz, which agrees well with the previous result recommended by Comite International des Poids et Mesures.
基金The project supported by National Natural Science Foundation of China under Grant Nos. 10475008, 10675170, and 10435020, and the Department of Nuclear Physics of China Institute of Atomic Energy under Grant Nos. 11SZZ-200501 and 11SZZ-200601
基金Project(2012BAF03B05)supported by the National Key Technology R&D Program of ChinaProject(61025015)supported by the National Natural Science Foundation for Distinguished Young Scholars of China+1 种基金Project(61273185)supported by the National Natural Science Foundation of ChinaProject(2012CK4018)supported by the Science and Technology Project of Hunan Province,China
文摘湿法炼锌浸出液中存在多金属组分,如Zn(Ⅱ)和Co(Ⅱ),针对重叠峰分离提出一种基于类Gaussian分布的线性扫描极谱重叠峰分离方法。通过分析线性扫描极谱曲线的特性构造类Gaussian分布作为待分离重叠峰子峰的模型,并利用多分辨率小波分解确定各子峰波峰和波谷位置,基于该模型及确定值对重叠峰及其导数峰进行非线性加权最小二乘(nonlinear weighted least squares,NWLS)拟合,根据重构参数将重叠峰分离为独立的子峰,实现该类重叠峰的分离。该类重叠峰分离的结果表明:多分辨率小波分解的分辨误差小于1%,NWLS拟合的分离精度高于96%,本方法可以有效分离Zn(Ⅱ)和Co(Ⅱ)产生的极谱重叠峰。
基金Project(2009CB320603)supported by the National Basic Research Program of ChinaProject(IRT0712)supported by Program for Changjiang Scholars and Innovative Research Team in University+1 种基金Project(B504)supported by the Shanghai Leading Academic Discipline ProgramProject(61174118)supported by the National Natural Science Foundation of China
文摘In order to reduce the computation of complex problems, a new surrogate-assisted estimation of distribution algorithm with Gaussian process was proposed. Coevolution was used in dual populations which evolved in parallel. The search space was projected into multiple subspaces and searched by sub-populations. Also, the whole space was exploited by the other population which exchanges information with the sub-populations. In order to make the evolutionary course efficient, multivariate Gaussian model and Gaussian mixture model were used in both populations separately to estimate the distribution of individuals and reproduce new generations. For the surrogate model, Gaussian process was combined with the algorithm which predicted variance of the predictions. The results on six benchmark functions show that the new algorithm performs better than other surrogate-model based algorithms and the computation complexity is only 10% of the original estimation of distribution algorithm.
