Estimation and detection algorithms for orthogonal frequency division multiplexing (OFDM) systems can be de-veloped based on the sum-product algorithms, which operate by message passing in factor graphs. In this paper...Estimation and detection algorithms for orthogonal frequency division multiplexing (OFDM) systems can be de-veloped based on the sum-product algorithms, which operate by message passing in factor graphs. In this paper, we apply the sampling method (Monte Carlo) to factor graphs, and then the integrals in the sum-product algorithm can be approximated by sums, which results in complexity reduction. The blind receiver for OFDM systems can be derived via Sequential Monte Carlo (SMC) in factor graphs, the previous SMC blind receiver can be regarded as the special case of the sum-product algorithms using sampling methods. The previous SMC blind receiver for OFDM systems needs generating samples of the channel vector assuming the channel has an a priori Gaussian distribution. In the newly-built blind receiver, we generate samples of the virtual-pilots instead of the channel vector, with channel vector which can be easily computed based on virtual-pilots. As the size of the vir-tual-pilots space is much smaller than the channel vector space, only small number of samples are necessary, with the blind de-tection being much simpler. Furthermore, only one pilot tone is needed to resolve phase ambiguity and differential encoding is not used anymore. Finally, the results of computer simulations demonstrate that the proposal can perform well while providing sig-nificant complexity reduction.展开更多
Online assessment of remaining useful life(RUL) of a system or device has been widely studied for performance reliability, production safety, system conditional maintenance, and decision in remanufacturing engineering...Online assessment of remaining useful life(RUL) of a system or device has been widely studied for performance reliability, production safety, system conditional maintenance, and decision in remanufacturing engineering. However,there is no consistency framework to solve the RUL recursive estimation for the complex degenerate systems/device.In this paper, state space model(SSM) with Bayesian online estimation expounded from Markov chain Monte Carlo(MCMC) to Sequential Monte Carlo(SMC) algorithm is presented in order to derive the optimal Bayesian estimation.In the context of nonlinear & non-Gaussian dynamic systems, SMC(also named particle filter, PF) is quite capable of performing filtering and RUL assessment recursively. The underlying deterioration of a system/device is seen as a stochastic process with continuous, nonreversible degrading. The state of the deterioration tendency is filtered and predicted with updating observations through the SMC procedure. The corresponding remaining useful life of the system/device is estimated based on the state degradation and a predefined threshold of the failure with two-sided criterion. The paper presents an application on a milling machine for cutter tool RUL assessment by applying the above proposed methodology. The example shows the promising results and the effectiveness of SSM and SMC online assessment of RUL.展开更多
A semi-analytical Monte Carlo (SMC) simulation was developed to simulate the propagation of laser-induced fluo- rescence (LIF) in an optically participating spray, which simultaneously exhibits spectrally dependent em...A semi-analytical Monte Carlo (SMC) simulation was developed to simulate the propagation of laser-induced fluo- rescence (LIF) in an optically participating spray, which simultaneously exhibits spectrally dependent emission, anisotropic scattering, absorption, and re-emission. The SMC simulation is described and then applied to an experimental configuration of a cloud of polydisperse droplets composed of water and sulforhodamine B dye. In the SMC simulation, the collected LIF flux on the remote receptor element is calculated as the global contribution from the emissive source, single, twice, … and nth collision events in any sequence. The effects on the fluorescence photons propagation of spray parameters like the dye concentration, droplets concentration, and droplets size are examined. Three spectral bands representing different optical properties are chosen to analyze the interference of absorption, scattering and re-emission on the detected LIF flux. The obtained spectral LIF flux distribution on the receptor demonstrates a “red shift” phenomenon.展开更多
In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of...In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of sub-synchronous oscillation(SSO)from the point view of the farm.This paper proposes a method of unstable SSO risk evaluation for grid-connected PMSG-based wind farms based on the sequential Monte Carlo simulation(SMCS).The determination of critical wind speed(CWS)of SSO and the sequential simulation strategy of wind speed states and PMSG states in a wind farm at the same wind speed(S-WF),as well as in a wind farm at different wind speeds(D-WF),are studied.Five indices evaluating the expectation,duration,frequency and energy loss of SsO risk are proposed.Moreover,a strategy to reduce SsO risk by adjusting the cut-in wind speed is discussed.The effectiveness of the discussed issues in this paper are proved by the case studies of a 750-PMSG wind farm based on the actual wind speed data collected.展开更多
In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library,a new Genetic Algorithm (GA)-based techniq...In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library,a new Genetic Algorithm (GA)-based technique is developed to determine the maximum power dissipation from a statistical point of view. The simulation on ISCAS-89 benchmarks shows that the ratio of the maximum power dissipation with glitching activity over the maximum power under zero-delay model ranges from 1.18 to 4.02. Compared with the traditional Monte Carlo-based technique, the new approach presented in this paper is more effective.展开更多
We propose an efficient measurement-driven sequential Monte Carlo multi-Bernoulli(SMC-MB) filter for multi-target filtering in the presence of clutter and missing detection. The survival and birth measurements are dis...We propose an efficient measurement-driven sequential Monte Carlo multi-Bernoulli(SMC-MB) filter for multi-target filtering in the presence of clutter and missing detection. The survival and birth measurements are distinguished from the original measurements using the gating technique. Then the survival measurements are used to update both survival and birth targets, and the birth measurements are used to update only the birth targets.Since most clutter measurements do not participate in the update step, the computing time is reduced significantly.Simulation results demonstrate that the proposed approach improves the real-time performance without degradation of filtering performance.展开更多
提出一种基于粒子概率假设密度滤波器(Sequential Monte Carlo probability hypothesis density filter,SMC-PHDF)的部分可分辨的群目标跟踪算法.该算法可直接获得群而非个体的个数和状态估计.这里群的状态包括群的质心状态和形状.为了...提出一种基于粒子概率假设密度滤波器(Sequential Monte Carlo probability hypothesis density filter,SMC-PHDF)的部分可分辨的群目标跟踪算法.该算法可直接获得群而非个体的个数和状态估计.这里群的状态包括群的质心状态和形状.为了估计群的个数和状态,该算法利用高斯混合模型(Gaussian mixture models,GMM)拟合SMC-PHDF中经重采样后的粒子分布,这里混合模型的元素个数和参数分别对应于群的个数和状态.期望最大化(Expectation maximum,EM)算法和马尔科夫链蒙特卡洛(Markov chain Monte Carlo,MCMC)算法分别被用于估计混合模型的参数.混合模型的元素个数可通过删除、合并及分裂算法得到.100次蒙特卡洛(Monte Carlo,MC)仿真实验表明该算法可有效跟踪部分可分辨的群目标.相比EM算法,MCMC算法能够更好地提取群的个数和状态,但它的计算量要大于EM算法.展开更多
针对具有空时分组码的多载波CDMA(Space Time Block Coding Multi Carrier Code Division Multiple Access,STBC-MC-CDMA)信号扩频码及信息序列的联合估计问题,结合序贯蒙特卡罗(Sequential Monte Carlo,SMC)算法和卡尔曼滤波技术,充分...针对具有空时分组码的多载波CDMA(Space Time Block Coding Multi Carrier Code Division Multiple Access,STBC-MC-CDMA)信号扩频码及信息序列的联合估计问题,结合序贯蒙特卡罗(Sequential Monte Carlo,SMC)算法和卡尔曼滤波技术,充分利用STBC和OFDM(Orthogonal Frequency Division Multiplexing)调制的正交属性,提出了一种快速的盲解扩算法.该算法通过将信号模型按不同符号路数和天线数目进行分段处理,采用卡尔曼滤波方法对均值和协方差进行迭代更新,并用一组带有权值的抽样粒子来近似建立的联合后验概率分布,根据抽样值和重要性权值大小进行参量状态估计,大大提高了算法的计算效率.理论分析和仿真结果验证了本文算法的有效性.展开更多
基金Project supported by the National Hi-Tech Research and Develop-ment Program (863) of China (No. 2003AA123310) and the National Natural Science Foundation of China (No. 60332030)
文摘Estimation and detection algorithms for orthogonal frequency division multiplexing (OFDM) systems can be de-veloped based on the sum-product algorithms, which operate by message passing in factor graphs. In this paper, we apply the sampling method (Monte Carlo) to factor graphs, and then the integrals in the sum-product algorithm can be approximated by sums, which results in complexity reduction. The blind receiver for OFDM systems can be derived via Sequential Monte Carlo (SMC) in factor graphs, the previous SMC blind receiver can be regarded as the special case of the sum-product algorithms using sampling methods. The previous SMC blind receiver for OFDM systems needs generating samples of the channel vector assuming the channel has an a priori Gaussian distribution. In the newly-built blind receiver, we generate samples of the virtual-pilots instead of the channel vector, with channel vector which can be easily computed based on virtual-pilots. As the size of the vir-tual-pilots space is much smaller than the channel vector space, only small number of samples are necessary, with the blind de-tection being much simpler. Furthermore, only one pilot tone is needed to resolve phase ambiguity and differential encoding is not used anymore. Finally, the results of computer simulations demonstrate that the proposal can perform well while providing sig-nificant complexity reduction.
基金Supported by Basic Research and Development Plan of China (973 Program,Grant Nos.2011CB013401,2011CB013402)Special Fundamental Research Funds for Central Universities of China(Grant No.DUT14QY21)
文摘Online assessment of remaining useful life(RUL) of a system or device has been widely studied for performance reliability, production safety, system conditional maintenance, and decision in remanufacturing engineering. However,there is no consistency framework to solve the RUL recursive estimation for the complex degenerate systems/device.In this paper, state space model(SSM) with Bayesian online estimation expounded from Markov chain Monte Carlo(MCMC) to Sequential Monte Carlo(SMC) algorithm is presented in order to derive the optimal Bayesian estimation.In the context of nonlinear & non-Gaussian dynamic systems, SMC(also named particle filter, PF) is quite capable of performing filtering and RUL assessment recursively. The underlying deterioration of a system/device is seen as a stochastic process with continuous, nonreversible degrading. The state of the deterioration tendency is filtered and predicted with updating observations through the SMC procedure. The corresponding remaining useful life of the system/device is estimated based on the state degradation and a predefined threshold of the failure with two-sided criterion. The paper presents an application on a milling machine for cutter tool RUL assessment by applying the above proposed methodology. The example shows the promising results and the effectiveness of SSM and SMC online assessment of RUL.
基金Project supported by the National Natural Science Foundation of China (No. 60534030)the Scholarship of French Embassy in China and the Doctoral Grant from French Embassy in China
文摘A semi-analytical Monte Carlo (SMC) simulation was developed to simulate the propagation of laser-induced fluo- rescence (LIF) in an optically participating spray, which simultaneously exhibits spectrally dependent emission, anisotropic scattering, absorption, and re-emission. The SMC simulation is described and then applied to an experimental configuration of a cloud of polydisperse droplets composed of water and sulforhodamine B dye. In the SMC simulation, the collected LIF flux on the remote receptor element is calculated as the global contribution from the emissive source, single, twice, … and nth collision events in any sequence. The effects on the fluorescence photons propagation of spray parameters like the dye concentration, droplets concentration, and droplets size are examined. Three spectral bands representing different optical properties are chosen to analyze the interference of absorption, scattering and re-emission on the detected LIF flux. The obtained spectral LIF flux distribution on the receptor demonstrates a “red shift” phenomenon.
基金supported by the National Natural Science Foundation of China under Grant(51777066).
文摘In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of sub-synchronous oscillation(SSO)from the point view of the farm.This paper proposes a method of unstable SSO risk evaluation for grid-connected PMSG-based wind farms based on the sequential Monte Carlo simulation(SMCS).The determination of critical wind speed(CWS)of SSO and the sequential simulation strategy of wind speed states and PMSG states in a wind farm at the same wind speed(S-WF),as well as in a wind farm at different wind speeds(D-WF),are studied.Five indices evaluating the expectation,duration,frequency and energy loss of SsO risk are proposed.Moreover,a strategy to reduce SsO risk by adjusting the cut-in wind speed is discussed.The effectiveness of the discussed issues in this paper are proved by the case studies of a 750-PMSG wind farm based on the actual wind speed data collected.
基金Supported by NSF of the United States under contract 5978 East Asia and Pacific Program 9602485
文摘In this paper, the glitching activity and process variations in the maximum power dissipation estimation of CMOS circuits are introduced. Given a circuit and the gate library,a new Genetic Algorithm (GA)-based technique is developed to determine the maximum power dissipation from a statistical point of view. The simulation on ISCAS-89 benchmarks shows that the ratio of the maximum power dissipation with glitching activity over the maximum power under zero-delay model ranges from 1.18 to 4.02. Compared with the traditional Monte Carlo-based technique, the new approach presented in this paper is more effective.
基金Project supported by the National Natural Science Foundationof China(Nos.61174142,61222310,and 61374021)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Nos.20120101110115 and 20130101110109)+3 种基金theZhejiang Provincial Science and Technology Planning Projects ofChina(No.2012C21044)the Marine Interdisciplinary ResearchGuiding Funds for Zhejiang University(No.2012HY009B)theFundamental Research Funds for the Central Universities(No.2014XZZX003-12)the Aeronautical Science Foundation ofChina(No.20132076002)
文摘We propose an efficient measurement-driven sequential Monte Carlo multi-Bernoulli(SMC-MB) filter for multi-target filtering in the presence of clutter and missing detection. The survival and birth measurements are distinguished from the original measurements using the gating technique. Then the survival measurements are used to update both survival and birth targets, and the birth measurements are used to update only the birth targets.Since most clutter measurements do not participate in the update step, the computing time is reduced significantly.Simulation results demonstrate that the proposed approach improves the real-time performance without degradation of filtering performance.
文摘提出一种基于粒子概率假设密度滤波器(Sequential Monte Carlo probability hypothesis density filter,SMC-PHDF)的部分可分辨的群目标跟踪算法.该算法可直接获得群而非个体的个数和状态估计.这里群的状态包括群的质心状态和形状.为了估计群的个数和状态,该算法利用高斯混合模型(Gaussian mixture models,GMM)拟合SMC-PHDF中经重采样后的粒子分布,这里混合模型的元素个数和参数分别对应于群的个数和状态.期望最大化(Expectation maximum,EM)算法和马尔科夫链蒙特卡洛(Markov chain Monte Carlo,MCMC)算法分别被用于估计混合模型的参数.混合模型的元素个数可通过删除、合并及分裂算法得到.100次蒙特卡洛(Monte Carlo,MC)仿真实验表明该算法可有效跟踪部分可分辨的群目标.相比EM算法,MCMC算法能够更好地提取群的个数和状态,但它的计算量要大于EM算法.
文摘针对具有空时分组码的多载波CDMA(Space Time Block Coding Multi Carrier Code Division Multiple Access,STBC-MC-CDMA)信号扩频码及信息序列的联合估计问题,结合序贯蒙特卡罗(Sequential Monte Carlo,SMC)算法和卡尔曼滤波技术,充分利用STBC和OFDM(Orthogonal Frequency Division Multiplexing)调制的正交属性,提出了一种快速的盲解扩算法.该算法通过将信号模型按不同符号路数和天线数目进行分段处理,采用卡尔曼滤波方法对均值和协方差进行迭代更新,并用一组带有权值的抽样粒子来近似建立的联合后验概率分布,根据抽样值和重要性权值大小进行参量状态估计,大大提高了算法的计算效率.理论分析和仿真结果验证了本文算法的有效性.
