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Complete q-Moment Convergence of moving average Processes under -mixing Assumption

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Journal of Mathematical Research and Exposition 2011年第4期31卷 687-697页

作者： Xing Cai ZHOU Jin Guan LIN Department of Mathematics Southeast University Jiangsu 210096 P. R. China Department of Mathematics and Computer Science Tongling University Anhui 244000 P. R. China

In this paper, we study the complete q-moment convergence of moving average processes under v-mixing assumption. The results obtained not only extend some previous known results, but also improve them.

关键词： moving average φ-mixing complete moment convergence.

moving average Barriers in Chinese Stock Markets

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Moving Average Barriers in Chinese Stock Markets

A Law of the Iterated Logarithm for moving average Processes

第十届海峡两岸统计与概率研讨会

作者： Li Yuanpeng Niu Jianjun Xiao Zhiguo Fudan University SHUFE

We find that the moving averages serve as psychological barriers of Chinese stock markets. Using a uniformity test and GARCH models, we establish the following facts. First, the Shanghai stock index doesn’t move continuously near the MA lines. Second, both the mean and volatility of the index return change signifi cantly while the index crosses the MA lines. To substantiate our fi ndings, we construct a technical trading strategy using MA rules. It turns out that the technical strategy outperform the passive buy-and-hold strategy by a large margin.

关键词： Psychological barriers moving average Technical trading rules Chinese stock markets

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Wuhan University Journal of Natural Sciences 1999年第1期4卷 10-12页

作者： Chen Pingyan Wu Jianmin Wuhan University College of Mathematical Sciences Wuhan China (GRID:grid.49470.3e) (ISNI:***) Huazhong University of Science and Technology Department of Computer Science Wuhan China (GRID:grid.33199.31) (ISNI:***)

Chover type law of iterated logarithm for moving average process of stable random variables with exponent α(0<α<1) was obtained.

关键词： stable distribution moving average LIL

Adaptability of n-γdiscrimination and filtering methods based on plastic scintillation

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Nuclear Science and Techniques 2021年第3期32卷 63-71页

作者： Zhuo Zuo Hao-Ran Liu Yu-Cheng Yan Bing-Qi Liu Song Zhang Chengdu University of Technology College of Engineering Technology Leshan 614000SichuanChina Southwest Institute of Physics Chengdu 610225China Chengdu University Chengdu 610106China Chengdu University of Technology Chengdu 610225China

Neutrons have been extensively used in many fields,such as nuclear physics,biology,geology,medical science,and national defense,owing to their unique penetration *** rays are usually accompanied by the detection of *** capability to discriminate neutrons from gamma rays is important for evaluating plastic scintillator neutron detectors because similar pulse shapes are generated from both forms of radiation in the detection *** pulse signals measured by plastic scintillators contain noise,which decreases the accuracy of n-y *** improve the performance of n-y discrimination,the noise of the pulse signals should be filtered before the n-y discrimination *** this study,the influences of the Fourier transform,wavelet transform,moving-average filter,and Kalman algorithm on the charge comparison method,fractal spectrum method,and back-propagation neural network methods were *** was found that the Fourier transform filtering algorithm exhibits better adaptability to the charge comparison method than others,with an increasing accuracy of 6.87%compared to that without the filtering ***,the Kalman filter offers an improvement of 3.04%over the fractal spectrum method,and the adaptability of the moving-average filter in backpropagation neural network discrimination is better than that in other methods,with an increase in 8.48%.The Kalman filtering algorithm has a significant impact on the peak value of the pulse,reaching 4.49%,and it has an insignificant impact on the energy resolution of the spectrum measurement after discrimination.

关键词： Fourier transform Wavelet transform moving average Kalman filter Charge comparison method Fractal spectrum method Back-propagation neural network

Spatial pyramidal cross correlation for particle image velocimetry

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Science China(Technological Sciences) 2018年第6期61卷 867-878页

作者： WANG HongPing WU Peng GAO Qi WANG JianJie WANG JinJun Key Laboratory of Fluid Mechanics Ministry of Education Beihang University Beoing 100083 China State Key Laboratory of Nonlinear Mechanics Institute of Mechanics Chinese Academy of Sciences Beoing 100190 China Artificial Organ Technology Laboratory Biomanufacturing Centre School of Mechanical and Electrical Engineering Soochow UniversitySuzhou 215006 China

A spatial pyramidal cross-correlation based on interrogation area sub-division is introduced to improve the measurement resolution in particle image velocimetry(PIV). The high-resolution velocity can be achieved with a velocity prediction model via coarse cross-correlation. The prediction formula is deduced from the frequency response of the moving average(MA). The performance of this method was assessed using synthetically generated images of sinusoidal shear flow, two-dimensional vortical cellular flow, and homogeneous turbulence. A real PIV experiment of turbulent boundary layer was used to evaluate the new method. The results indicate that the spatial pyramid cross-correlation can robustly increase the spatial resolution.

关键词： particle image velocimetry (PIV) cross correlation spatial resolution moving average

Efficient co-channel interference suppression in MIMO-OFDM systems

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Science China(Information Sciences) 2015年第2期58卷 116-130页

作者： MENG Xin JIANG Bin GAO XiQi National Mobile Communications Research Laboratory Southeast University

In this paper, we investigate channel frequency response(CFR) matrix and interference-plus-noise covariance matrix(ICM) estimation in multiple-input multiple-output(MIMO) and orthogonal frequency division multiplexing(OFDM) systems to suppress co-channel interference at the receiver side. We employ least square criterion to perform the initial CFR estimation. Then we estimate the autocorrelation function of interference-plus-noise in the time domain, instead of estimating the ICM in the frequency domain *** autocorrelation function estimation has two steps. Firstly, we present the inherent relationship between the expectation of the sample autocorrelation function of the residual(SAFR) and the true autocorrelation function, which is actually a linear transformation. Based on this, we propose a compensating method. This compensation brings significant performance gains when the pilot OFDM symbol number is small. Secondly,since the compensated SAFR cannot be guaranteed to be an autocorrelation sequence(ACS), which will make the obtained ICM loss the positive semidefinite property, we utilize semidefinite programming(SDP) to find an ACS that is the nearest to the compensated SAFR. The SDP is solved in its dual form, which yields a significant reduced complexity. Finally the estimated ICM is reutilized to revise the CFR estimation. The estimated CFR and ICM show excellent interference suppression performances when being applied in an interference rejection combining receiver.

关键词： MIMO-OFDM channel estimation co-channel interference interference-plus-noise covariance ma-trix moving average autocorrelation sequence semidefinite programming interference rejection combining

Discount Rate of China’s New Energy Power Industry

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Energy Engineering 2022年第1期119卷 315-329页

作者： Yafei Rong Xudong Sun School of Management China University of Mining and Technology(Beijing)Beijing100083China State Key Laboratory of Coal Resources and Safe Mining China University of Mining and Technology(Beijing)Beijing100083China

Under the dual pressures of energy crisis and environmental pollution,China’s new energy power industry has become a focal point for environmental management and requires greater *** this context,as a significant input of investment projects,discount rate requires a well-calibrated evaluation because new energy power investment projects are highly capital *** main objective of this paper is to evaluate the discount rate of China’s new energy power ***,we use moving average to correct the parameters of capital asset pricing model(CAPM)and weighted average cost of capital,which extends the literature on the avoidance of CAPM noise information ***,we study the industry-level annual discount rates of mainly China’s new energy power industries,including hydropower,nuclear power,wind power,and photovoltaic power industries for the period of *** results show that discount rates in China’s new energy power industries evolved differently between the years of 2014-2019 with average annual discount rates being 7.56%,5.83%,5.60%,and 8.64%,for the hydropower,nuclear power,wind power,and photovoltaic power industries,*** 2019,the four annual discount rates were highest for the photovoltaic power industry(8.66%),followed by hydropower(7.17%),wind power(5.72%),and nuclear power industry(5.26%).Forecasting to 2020 from the 2019 evaluation base period,the discount rates are 6.37%,5.00%,6.57%,and 9.05%for the photovoltaic power,hydropower,wind power,and nuclear power industries,*** the different capital structures,their forecasts for the photovoltaic power,hydropower,wind power,and nuclear power industries in 2020 are,respectively,within[4.35%,9.24%],[3.92%,7.10%],[4.58%,10.40%],[5.46%,14.81%].We also discussed more details on capital structure and forecast period of discount rates for China’s new energy power *** analysis shows that it is necessary to establish a new energy power industry databa

关键词： Discount rate China’s new energy power industry moving average capital asset price model weighted average cost of capital

Climate instability during the last glaciation recorded in the Yuanbu loess section

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Progress in Natural Science:Materials International 2009年第4期19卷 453-459页

作者： Yimeng Chen Department of Economics & Management, Huizhou University, Huizhou 516007, China Department of Economics & Management Huizhou University Huizhou 516007 China

Abrupt events within the Linxia Yuanbu loess section in the western Loess Plateau in China were investigated. The climatic proxy index of the content of mean grain-size and >4 lm grain-size fraction of the section was used as a climatic indicator, and a moving average method was applied in the statistical analysis to extract the abrupt events recorded in the section. It was found that the loess of the last glaciation recorded not only the abrupt events teleconnected with the high-latitude North Atlantic and Greenland regions but also as many as 15 abrupt events in addition to the Heinrich (H) and Younger Dryas (YD) events. This indicates that abrupt climate changes were typical of the climate changes occurring in the Loess Plateau during the last glaciation. The widely recognized mechanisms of the abrupt climate changes, including the heat transfer theory of the North Atlantic Ocean, the atmospheric circulation theory, and the theory of the interac- tion between low-latitude ocean and the atmosphere remains to be discussed. Perhaps this problem could be resolved by revealing the rela- tion between the evolution of the features of the East Asian monsoon climate and the climate in the surrounding areas. Through a detailed study of the features of the Heinrich and YD events, criteria on which the abrupt events recorded in the loess could be distinguished were tentatively defined. The events were associated with a large grain size, high carbonate content, high lightness, low susceptibility, low redness and low yellowness. In addition, the variation amplitude of the adjacent peak and valley on the curve of the content of the mean grain-size and >40 lm grain-size fraction was larger than 3.4 lm and the content of >40 lm grain-size fraction was larger than 2.0 lm. Lastly, the length of the variation time was less than 500 years. If all these criteria were met, the event was viewed as an abrupt event.

关键词： Climate instability moving average Abrupt event Last glaciation Loess section

Reliability Prediction Method Based on State Space Model for Rolling Element Bearing

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Journal of Shanghai Jiaotong university(Science) 2015年第3期20卷 317-321页

作者：李宏坤张志新李秀刚任远杰 Dalian Xinyu Science Technology Development Center Co. Ltd. School of Mechanical Engineering Dalian University Shenyang Blower Works Group Corporation

Reliability analysis based on equipment's performance degradation characteristics is one of the significant research areas in reliability research. Nowadays, many researches are carried on multi-sample analysis. But it is limited for a single equipment reliability prediction. Therefore, the method of reliability prediction based on state space model(SSM) is proposed in this research. Feature energy of the monitored signals is extracted with the wavelet packet analysis and the associated frequency band energy with online monitored data. Then,degradation feature is improved by moving average filtering processing taken as input pair model parameter of SSM to be estimated. In the end, state space predicting model of degradation index is established. The probability density distribution of the degradation index is predicted, and the degree of reliability is calculated. A real testing example of bearing is used to demonstrate the rationality and effectiveness of this method. It is a useful method for single sample reliability prediction.

关键词： reliability prediction state space model feature extraction wavelet analysis moving average