相干布局囚禁(Coherent Population Trapping,CPT)原子频标是一种功耗低、体积小、启动快的新型原子频标,温控系统是影响CPT原子频标稳定度指标的重要环节.本文介绍了通过优化设计实现CPT原子频标的高性能温控系统的方案.通过仪表放大...相干布局囚禁(Coherent Population Trapping,CPT)原子频标是一种功耗低、体积小、启动快的新型原子频标,温控系统是影响CPT原子频标稳定度指标的重要环节.本文介绍了通过优化设计实现CPT原子频标的高性能温控系统的方案.通过仪表放大器的应用提高了前端温度采集电路的温度分辨能力;通过小波分析算法对温度信号进行降噪处理;通过Δ-Σ算法实现脉冲宽度调制(Pulse Width Modulation,PWM),提高温控输出调节精度并减小谐波干扰.基于该方案实现了体积小、功耗低的温控电路,获得了较好的控温效果,改善了CPT原子频标频率稳定度指标.展开更多
In order to reduce the hidden danger of noise which can be charactered by singularity spectrum, a new algorithm based on wavelet transform modulus maxima method was proposed. Singularity analysis is one of the most pr...In order to reduce the hidden danger of noise which can be charactered by singularity spectrum, a new algorithm based on wavelet transform modulus maxima method was proposed. Singularity analysis is one of the most promising new approaches for extracting noise hidden information from noisy time series . Because of singularity strength is hard to calculate accurately, a wavelet transform modulus maxima method was used to get singularity spectrum. The singularity spectrum of white noise and aluminium interconnection electromigration noise was calculated and analyzed. The experimental results show that the new algorithm is more accurate than tradition estimating algorithm. The proposed method is feasible and efficient.展开更多
It＇ s a problem to be solved how to de-noise the signal of blast shock wave overpressure. In the conventional methods, the high frequency of the signal is cut directly by some mathematics algorithms, such as Fourier ...It＇ s a problem to be solved how to de-noise the signal of blast shock wave overpressure. In the conventional methods, the high frequency of the signal is cut directly by some mathematics algorithms, such as Fourier Transform, but some of the useful signal will be cut together. We adopt a new method for the signal de-noising of shock wave overpressure by wavelet analysis, There are four steps in this method. Firstly, the original signal is de-compoed. Then the time-frequency features of the signal and noise are analyzed. Thirdly, the noise is separated from the signal by only cutting its frequency while the useful signal frequency is reserved as much as possible. Lastly, the useful signal with least loss of information is recovered by reconstruction process. To verify this method, a blast shock wave signal is de-noised with FFF to make a comparison. The results show that the signal de-noised by wavelet analysis approximates the ideal signal well.展开更多
In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavele...In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.展开更多
This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This d...This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This distribution of SINR can be used to make an analysis of average sum-rate,outage probability,and symbol error rate of massive MIMO downlink with MF at BS.From simulation,it is found that the derived approximate analytical expression for PDF of SINR is consistent with the simulated exact PDF from the definition of SINR in medium-scale and large-scale MIMO systems.展开更多
In the research of elastic wave signal detection algorithm, a method based on adaptive wavelet analysis and segmentation threshold processing of the channel noise removal methods is suggested to overcome the effect of...In the research of elastic wave signal detection algorithm, a method based on adaptive wavelet analysis and segmentation threshold processing of the channel noise removal methods is suggested to overcome the effect of noise, which is prcduced by absorption loss, scattering loss, reflection loss and multi-path effect during the elastic wave in the transmission undelgroound. The method helps to realize extraction and recovery of weak signal of elastic wave from the multi-path channel, and simulation study is carded out about wavelet de-noising effects of the elastic wave and obtained satisfactory results.展开更多
Ambient noise tomography is a rapidly emerging field of seismological research. This paper presents the current status of ambient noise data processing and its development history over the past several years, with the...Ambient noise tomography is a rapidly emerging field of seismological research. This paper presents the current status of ambient noise data processing and its development history over the past several years, with the intention to explain and justify this development through salient examples. The ambient noise data processing procedure can be divided into four principal phases： ① single station data preparation; ② cross- correlation and temporal stacking; ③ measurements of dispersion curves （ performed with frequency-time analysis for both group and phase speeds） ; ④ quality control, including SNR analysis and selection of the acceptable measurements. In addition, we provide a specific solution for a better use of the seismic station data to ambient noise study.展开更多
White noise deconvolution or input white noise estimation problem has important appli-cation backgrounds in oil seismic exploration,communication and signal processing.By the modern time series analysis method,based o...White noise deconvolution or input white noise estimation problem has important appli-cation backgrounds in oil seismic exploration,communication and signal processing.By the modern time series analysis method,based on the Auto-Regressive Moving Average(ARMA) innovation model,under the linear minimum variance optimal fusion rules,three optimal weighted fusion white noise deconvolution estimators are presented for the multisensor systems with time-delayed measurements and colored measurement noises.They can handle the input white noise fused filtering,prediction and smoothing problems.The accuracy of the fusers is higher than that of each local white noise estimator.In order to compute the optimal weights,the formula of computing the local estimation error cross-covariances is given.A Monte Carlo simulation example for the system with 3 sensors and the Bernoulli-Gaussian input white noise shows their effectiveness and performances.展开更多
Cryo-electron microscopy (cryo-EM) plays an important role in determining the structure of proteins, viruses, and even the whole cell. It can capture dynamic structural changes of large protein complexes, which other ...Cryo-electron microscopy (cryo-EM) plays an important role in determining the structure of proteins, viruses, and even the whole cell. It can capture dynamic structural changes of large protein complexes, which other methods such as X-ray crystallography and nuclear magnetic resonance analysis find difficult. The signal-to-noise ratio of cryo-EM images is low and the contrast is very weak, and therefore, the images are very noisy and require filtering. In this paper, a filtering method based on non-local means and Zernike moments is proposed. The method takes into account the rotational symmetry of some biological molecules to enhance the signal-to-noise ratio of cryo-EM images. The method may be useful in cryo-EM image processing such as the automatic selection of particles, orientation determination, and the building of initial models.展开更多
文摘相干布局囚禁(Coherent Population Trapping,CPT)原子频标是一种功耗低、体积小、启动快的新型原子频标,温控系统是影响CPT原子频标稳定度指标的重要环节.本文介绍了通过优化设计实现CPT原子频标的高性能温控系统的方案.通过仪表放大器的应用提高了前端温度采集电路的温度分辨能力;通过小波分析算法对温度信号进行降噪处理;通过Δ-Σ算法实现脉冲宽度调制(Pulse Width Modulation,PWM),提高温控输出调节精度并减小谐波干扰.基于该方案实现了体积小、功耗低的温控电路,获得了较好的控温效果,改善了CPT原子频标频率稳定度指标.
基金Foundation item: National Natural Science Foundation of China(No.60372072)
文摘In order to reduce the hidden danger of noise which can be charactered by singularity spectrum, a new algorithm based on wavelet transform modulus maxima method was proposed. Singularity analysis is one of the most promising new approaches for extracting noise hidden information from noisy time series . Because of singularity strength is hard to calculate accurately, a wavelet transform modulus maxima method was used to get singularity spectrum. The singularity spectrum of white noise and aluminium interconnection electromigration noise was calculated and analyzed. The experimental results show that the new algorithm is more accurate than tradition estimating algorithm. The proposed method is feasible and efficient.
文摘It＇ s a problem to be solved how to de-noise the signal of blast shock wave overpressure. In the conventional methods, the high frequency of the signal is cut directly by some mathematics algorithms, such as Fourier Transform, but some of the useful signal will be cut together. We adopt a new method for the signal de-noising of shock wave overpressure by wavelet analysis, There are four steps in this method. Firstly, the original signal is de-compoed. Then the time-frequency features of the signal and noise are analyzed. Thirdly, the noise is separated from the signal by only cutting its frequency while the useful signal frequency is reserved as much as possible. Lastly, the useful signal with least loss of information is recovered by reconstruction process. To verify this method, a blast shock wave signal is de-noised with FFF to make a comparison. The results show that the signal de-noised by wavelet analysis approximates the ideal signal well.
基金Supported by the National High-Tech Research and De-velopment Plan (863) of China (No.2006AA01Z232, No.2009AA01Z212, No.200901Z202)the Natural Science Foundation of Jiangsu Province (No. BK2007603)+2 种基金High-Tech Research Plan of Jiangsu Province (No.BG2007045)Research Climbing Project of NJUPT (No.NY2007044)Foundation of Nanjing University of Information Science and Technology(No.20070025)
文摘In this letter, we present a novel approach of valve stiction detection using wavelet technology. A new non-invasive method is developed with the closed-loop normal operating data. The redundant dyadic discrete wavelet transform is used to decompose the data at different resolution scales. Based on the Lipschitz regularity theory, wavelet coefficients analysis across scales is performed to detect the jumps in the controlled variables. Adaptive wavelet de-noising is then applied to the data. Features of the valve stiction patterns are extracted from the de-noised data and the valve stiction probability is calculated.
基金Supported by the National Natural Science Foundation of China(No.61271230,61301107)the Fundamental Research Funds for the Central Universities(No.30920130122004)Open Research Fund of National Mobile Communications Research Laboratory,Southeast University(No.2013D02)
文摘This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This distribution of SINR can be used to make an analysis of average sum-rate,outage probability,and symbol error rate of massive MIMO downlink with MF at BS.From simulation,it is found that the derived approximate analytical expression for PDF of SINR is consistent with the simulated exact PDF from the definition of SINR in medium-scale and large-scale MIMO systems.
文摘In the research of elastic wave signal detection algorithm, a method based on adaptive wavelet analysis and segmentation threshold processing of the channel noise removal methods is suggested to overcome the effect of noise, which is prcduced by absorption loss, scattering loss, reflection loss and multi-path effect during the elastic wave in the transmission undelgroound. The method helps to realize extraction and recovery of weak signal of elastic wave from the multi-path channel, and simulation study is carded out about wavelet de-noising effects of the elastic wave and obtained satisfactory results.
基金Jointly funded by the Natural Science Foundation of China(40774018)the Seismic Scientific and Technological Spark Project,China Earthquake Administration(XH13009Y)the Earthquake Research Foundation,Earthquake Administration of Anhui Province(20120702)
文摘Ambient noise tomography is a rapidly emerging field of seismological research. This paper presents the current status of ambient noise data processing and its development history over the past several years, with the intention to explain and justify this development through salient examples. The ambient noise data processing procedure can be divided into four principal phases： ① single station data preparation; ② cross- correlation and temporal stacking; ③ measurements of dispersion curves （ performed with frequency-time analysis for both group and phase speeds） ; ④ quality control, including SNR analysis and selection of the acceptable measurements. In addition, we provide a specific solution for a better use of the seismic station data to ambient noise study.
基金Supported by the National Natural Science Foundation of China (No.60874063)Science and Technology Re-search Foundation of Heilongjiang Education Department (No.11523037)
文摘White noise deconvolution or input white noise estimation problem has important appli-cation backgrounds in oil seismic exploration,communication and signal processing.By the modern time series analysis method,based on the Auto-Regressive Moving Average(ARMA) innovation model,under the linear minimum variance optimal fusion rules,three optimal weighted fusion white noise deconvolution estimators are presented for the multisensor systems with time-delayed measurements and colored measurement noises.They can handle the input white noise fused filtering,prediction and smoothing problems.The accuracy of the fusers is higher than that of each local white noise estimator.In order to compute the optimal weights,the formula of computing the local estimation error cross-covariances is given.A Monte Carlo simulation example for the system with 3 sensors and the Bernoulli-Gaussian input white noise shows their effectiveness and performances.
基金supported by the National Basic Research Program of China (2010CB912400)
文摘Cryo-electron microscopy (cryo-EM) plays an important role in determining the structure of proteins, viruses, and even the whole cell. It can capture dynamic structural changes of large protein complexes, which other methods such as X-ray crystallography and nuclear magnetic resonance analysis find difficult. The signal-to-noise ratio of cryo-EM images is low and the contrast is very weak, and therefore, the images are very noisy and require filtering. In this paper, a filtering method based on non-local means and Zernike moments is proposed. The method takes into account the rotational symmetry of some biological molecules to enhance the signal-to-noise ratio of cryo-EM images. The method may be useful in cryo-EM image processing such as the automatic selection of particles, orientation determination, and the building of initial models.
