In this paper,we use the double difference location method based on waveform crosscorrelation algorithm for precise positioning of the Three Gorges Reservoir( TGR)earthquakes and analysis of seismic activity. First,we...In this paper,we use the double difference location method based on waveform crosscorrelation algorithm for precise positioning of the Three Gorges Reservoir( TGR)earthquakes and analysis of seismic activity. First,we use the bi-spectrum cross-correlation method to analyze the seismic waveform data of TGR encrypted networks from March,2009 to December,2010,and evaluate the quality of waveform cross-correlation analysis.Combined with the waveform cross-correlation of data obtained, we use the double difference method to relocate the earthquake position. The results show that location precision using bi-spectrum verified waveform cross-correlation data is higher than that by using other types of data,and the mean 2 sig-error in EW,NS and UD are 3.2 m,3.9 m and 6.2 m,respectively. For the relocation of the Three Gorges Reservoir earthquakes,the results show that the micro-earthquakes along the Shenlongxi river in the Badong reservoir area obviously show the characteristics of three linear zones with nearly east-west direction,which is in accordance with the small faults and carbonate strata line of the neotectonic period,revealing the reservoir water main along the underground rivers or caves permeated and induced seismic activity. The stronger earthquakes may have resulted from small earthquakes through the active layers.展开更多
Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with ot...Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.展开更多
To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ens...To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.展开更多
"Repeating earthquakes",identified by cross-correlation of seismic waveforms,are found to be much more abundant in the nature than conventionally expected. In recent years, with the development of digital se..."Repeating earthquakes",identified by cross-correlation of seismic waveforms,are found to be much more abundant in the nature than conventionally expected. In recent years, with the development of digital seismic networks, waveform cross correlation and "repeating earthquakes"have caused much attention to the measuring the variation of crustal medium properties and estimation of location accuracy and fault slip rate at depth or earthquake recurrence intervals. Moreover, as a useful tool, the "repeating earthquake" approach has also been used in the assessment of the accuracy of seismic phase picking,hypocenter location,fault structure and physics of earthquake sources,as well as the study of earthquake prediction. In this paper, we summarized the latest research and applications of "repeating earthquakes".展开更多
The elastic thickness parameter was estimated using the mobile correlation technique between the observed isostatic disturbance and the gravity disturbance calculated through direct gravimetric modeling. We computed t...The elastic thickness parameter was estimated using the mobile correlation technique between the observed isostatic disturbance and the gravity disturbance calculated through direct gravimetric modeling. We computed the vertical flexure value of the crust for a specific elastic thickness using a given topographic dataset. The gravity disturbance due to the topography was determined after the calculation. A grid of values for the elastic thickness parameter was generated. Then, a moving correlation was performed between the observed gravity data(representing actual surface data) and the calculated data from the forward modeling. The optimum elastic thickness of the particular point corresponded to the highest correlation coefficient. The methodology was tested on synthetic data and showed that the synthetic depth closely matched the original depth, including the elastic thickness value. To validate the results, the described procedure was applied to a real dataset from the Barreirinhas Basin, situated in the northeastern region of Brazil. The results show that the obtained crustal depth is highly correlated with the depth from known models. Additionally, we noted that the elastic thickness behaves as expected, decreasing from the continent towards the ocean. Based on the results, this method has the potential to be employed as a direct estimate of crustal depth and elastic thickness for any region.展开更多
This document presents a framework for recognizing people by palm vein distribution analysis using cross-correlation based signatures to obtain descriptors. Haar wavelets are useful in reducing the number of features ...This document presents a framework for recognizing people by palm vein distribution analysis using cross-correlation based signatures to obtain descriptors. Haar wavelets are useful in reducing the number of features while maintaining high recognition rates. This experiment achieved 97.5% of individuals classified correctly with two levels of Haar wavelets. This study used twelve-version of RGB and NIR (near infrared) wavelength images per individual. One hundred people were studied;therefore 4,800 instances compose the complete database. A Multilayer Perceptron (MLP) was trained to improve the recognition rate in a k-fold cross-validation test with k = 10. Classification results using MLP neural network were obtained using Weka (open source machine learning software).展开更多
The temperature change and rate of CO2 change are correlated with a time lag, as reported in a previous paper. The correlation was investigated by calculating a correlation coefficient r of these changes for selected ...The temperature change and rate of CO2 change are correlated with a time lag, as reported in a previous paper. The correlation was investigated by calculating a correlation coefficient r of these changes for selected ENSO events in this study. Annual periodical increases and decreases in the CO2 concentration were considered, with a regular pattern of minimum values in August and maximum values in May each year. An increased deviation in CO2 and temperature was found in response to the occurrence of El Niño, but the increase in CO2 lagged behind the change in temperature by 5 months. This pattern was not observed for La Niña events. An increase in global CO2 emissions and a subsequent increase in global temperature proposed by IPCC were not observed, but an increase in global temperature, an increase in soil respiration, and a subsequent increase in global CO2 emissions were noticed. This natural process can be clearly detected during periods of increasing temperature specifically during El Niño events. The results cast strong doubts that anthropogenic CO2 is the cause of global warming.展开更多
Waveform generation and digitization play essential roles in numerous physics experiments.In traditional distributed systems for large-scale experiments,each frontend node contains an FPGA for data preprocessing,which...Waveform generation and digitization play essential roles in numerous physics experiments.In traditional distributed systems for large-scale experiments,each frontend node contains an FPGA for data preprocessing,which interfaces with various data converters and exchanges data with a backend central processor.However,the streaming readout architecture has become a new paradigm for several experiments benefiting from advancements in data transmission and computing technologies.This paper proposes a scalable distributed waveform generation and digitization system that utilizes fiber optical connections for data transmission between frontend nodes and a central processor.By utilizing transparent transmission on top of the data link layer,the clock and data ports of the converters in the frontend nodes are directly mapped to the FPGA firmware at the backend.This streaming readout architecture reduces the complexity of frontend development and maintains the data conversion in proximity to the detector.Each frontend node uses a local clock for waveform digitization.To translate the timing information of events in each channel into the system clock domain within the backend central processing FPGA,a novel method is proposed and evaluated using a demonstrator system.展开更多
This paper establishes an amplitude modulation heating model, simulating the far-field radiation of ELF/VLF signals generated by modulation heating, as well as the specific location and longitudinal extent of the radi...This paper establishes an amplitude modulation heating model, simulating the far-field radiation of ELF/VLF signals generated by modulation heating, as well as the specific location and longitudinal extent of the radiation source. We consider various modulation waveforms and find that square-wave modulation has the highest excitation efficiency for ELF/VLF signals, and that square-wave modulation with a smaller duty cycle(<50%) exhibits higher excitation efficiency for ELF/VLF signals, while the sin^(2)t waveform modulation yields the lowest proportion of harmonic energy in the generated signals. The amplitude of the second harmonic generated by the sin^(2)t waveform is less than one-tenth that of the fundamental frequency, and the energy of higher-frequency harmonics can be negligibly small compared with those of the fundamental wave. It is a challenging task to achieve a balance between enhancing the excitation efficiency of ELF/VLF signals and also suppressing harmonics generated by the modulated heating process. This is because the harmonics are correspondingly enhanced as the excitation efficiency of the signals is increased. However, we find that under conditions of varying effective radiant power and modulation frequency, as long as the modulation waveform is unchanged, the energy ratio between the fundamental frequency signal generated by modulated heating and each harmonic is relatively fixed, with changes only in signal intensity and the location of the radiation source zone. This implies that one can first select modulation waveforms that make the signal less prone to distortion, then increase the effective radiated power to enhance the signal strength, without concern for harmonic interference of the fundamental signal.展开更多
Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation f...Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.展开更多
Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time se...Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.展开更多
In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(...In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(RSCCT)for BOC(kn,n)signals is proposed.In this paper,the principle of signal decomposition is combined with the traditional acquisition algorithm structure,and then based on the method of reconstructing the correlation function.The method firstly gets the sub-pseudorandom noise(PRN)code by decomposing the local PRN code,then uses BOC(kn,n)and the sub-PRN code cross-correlation to get the sub cross-correlation function.Finally,the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed.The simulation shows that RSCCT can completely eliminate the side peaks of BOC(kn,n)group signals while maintaining the narrow correlation of BOC,and its computational complexity is equivalent to sub carrier phase cancellation(SCPC)and autocorrelation side-peak cancellation technique(ASPeCT),and it reduces the computational complexity relative to BPSK-like.For BOC(n,n),the acquisition sensitivity of RSCCT is 3.25 dB,0.81 dB and 0.25 dB higher than binary phase shift keying(BPSK)-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.91,3.0 and 3.7 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.For BOC(2n,n),the acquisition sensitivity of RSCCT is 5.5 dB,1.25 dB and 2.69 dB higher than BPSK-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.02,1.68 and 2.12 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.展开更多
This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then clou...This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.展开更多
In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads o...In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject's brain function is healthy or not.展开更多
Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven method...Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.展开更多
The algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an e...The algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an effective algorithm for particle identification from consecutive images, the accurate velocity vector field can be obtained. The real velocity field in a valve chamber was measured by BICC in this study. From the full-field velocity information, the pressure and vorticity fields were also extracted by post-processing. (Edited author abstract) 6 Refs.展开更多
The amount of seismological data is rapidly increasing with accumulating observational time and increasing number of stations, requiring modern technique to provide adequate computing power. In present study, we propo...The amount of seismological data is rapidly increasing with accumulating observational time and increasing number of stations, requiring modern technique to provide adequate computing power. In present study, we proposed a framework to calculate large-scale noise crosscorrelation functions(NCFs) using public cloud service from ALIYUN. The entire computation is factorized into small pieces which are performed parallelly on specified number of virtual servers provided by the cloud. Using data from most seismic stations in China, five NCF databases are built. The results show that, comparing to the time cost using a single server, the entire time can be reduced over two orders of magnitude depending number of evoked virtual servers. This could reduce computation time from months to less than 12 hours. Based on obtained massive NCFs, the global body waves are retrieved through array interferometry and agree well with those from earthquakes. This leads to a solution to process massive seismic dataset within an affordable time and is applicable to other large-scale computing in seismological researches.展开更多
In this letter, with the synthesis of usual cross-correlation detecting method andchaotic detecting method, a new detecting system for the weak periodic pulse signal is constituted,in which the two methods can play re...In this letter, with the synthesis of usual cross-correlation detecting method andchaotic detecting method, a new detecting system for the weak periodic pulse signal is constituted,in which the two methods can play respective preponderance. Theoretical analyses and simulationstudies have shown that the detecting system is very sensitive to the periodic pulse signal understrong noise background and has exceedingly powerful capability of suppressing complex noise.展开更多
This paper shows the Fokker-Planck equation of a dynamical system driven by coloured cross-correlated white noises in the absence and presence of a small external force. Based on the Fokker-Planck equation and the def...This paper shows the Fokker-Planck equation of a dynamical system driven by coloured cross-correlated white noises in the absence and presence of a small external force. Based on the Fokker-Planck equation and the definition of Shannon's information entropy, the time dependence of entropy flux and entropy production can be calculated. The present results can be used to explain the extremal behaviour of time dependence of entropy flux and entropy production in view of the dissipative parameter γ of the system, coloured cross-correlation time τ and coloured cross-correlation strength λ.展开更多
An improved method that brings enhancement in accuracy for the interrogation of (digital) PIV images is described in this paper. This method is based on cross-correlation with discrete window offset, which makes use o...An improved method that brings enhancement in accuracy for the interrogation of (digital) PIV images is described in this paper. This method is based on cross-correlation with discrete window offset, which makes use of a translation of the second interrogation window and rebuilds it considering rotation and shear. The displacement extracted from PIV images is predicted and corrected by means of an iterative procedure. In addition, the displacement vectors are validated at each intermediate of the iteration process. The present improved cross-correlation method is compared with the conventional one in accuracy by interrogation of synthetic and real (digital) PIV images and the interrogation results are discussed.展开更多
基金funded by the National Science and Technology Pillar Program(2008BAC38B04)the Special Research Fund for Seismology(16A44ZX282)
文摘In this paper,we use the double difference location method based on waveform crosscorrelation algorithm for precise positioning of the Three Gorges Reservoir( TGR)earthquakes and analysis of seismic activity. First,we use the bi-spectrum cross-correlation method to analyze the seismic waveform data of TGR encrypted networks from March,2009 to December,2010,and evaluate the quality of waveform cross-correlation analysis.Combined with the waveform cross-correlation of data obtained, we use the double difference method to relocate the earthquake position. The results show that location precision using bi-spectrum verified waveform cross-correlation data is higher than that by using other types of data,and the mean 2 sig-error in EW,NS and UD are 3.2 m,3.9 m and 6.2 m,respectively. For the relocation of the Three Gorges Reservoir earthquakes,the results show that the micro-earthquakes along the Shenlongxi river in the Badong reservoir area obviously show the characteristics of three linear zones with nearly east-west direction,which is in accordance with the small faults and carbonate strata line of the neotectonic period,revealing the reservoir water main along the underground rivers or caves permeated and induced seismic activity. The stronger earthquakes may have resulted from small earthquakes through the active layers.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 11875042 and 11505114)the Shanghai Project for Construction of Top Disciplines (Grant No. USST-SYS-01)。
文摘Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.
基金supported by National Natural Science Foundation of China(No.61973234)Tianjin Science and Technology Plan Project(No.22YDTPJC00090)。
文摘To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.
基金funded by the Spark Program of China Earthquake Administration (XH1006)
文摘"Repeating earthquakes",identified by cross-correlation of seismic waveforms,are found to be much more abundant in the nature than conventionally expected. In recent years, with the development of digital seismic networks, waveform cross correlation and "repeating earthquakes"have caused much attention to the measuring the variation of crustal medium properties and estimation of location accuracy and fault slip rate at depth or earthquake recurrence intervals. Moreover, as a useful tool, the "repeating earthquake" approach has also been used in the assessment of the accuracy of seismic phase picking,hypocenter location,fault structure and physics of earthquake sources,as well as the study of earthquake prediction. In this paper, we summarized the latest research and applications of "repeating earthquakes".
文摘The elastic thickness parameter was estimated using the mobile correlation technique between the observed isostatic disturbance and the gravity disturbance calculated through direct gravimetric modeling. We computed the vertical flexure value of the crust for a specific elastic thickness using a given topographic dataset. The gravity disturbance due to the topography was determined after the calculation. A grid of values for the elastic thickness parameter was generated. Then, a moving correlation was performed between the observed gravity data(representing actual surface data) and the calculated data from the forward modeling. The optimum elastic thickness of the particular point corresponded to the highest correlation coefficient. The methodology was tested on synthetic data and showed that the synthetic depth closely matched the original depth, including the elastic thickness value. To validate the results, the described procedure was applied to a real dataset from the Barreirinhas Basin, situated in the northeastern region of Brazil. The results show that the obtained crustal depth is highly correlated with the depth from known models. Additionally, we noted that the elastic thickness behaves as expected, decreasing from the continent towards the ocean. Based on the results, this method has the potential to be employed as a direct estimate of crustal depth and elastic thickness for any region.
文摘This document presents a framework for recognizing people by palm vein distribution analysis using cross-correlation based signatures to obtain descriptors. Haar wavelets are useful in reducing the number of features while maintaining high recognition rates. This experiment achieved 97.5% of individuals classified correctly with two levels of Haar wavelets. This study used twelve-version of RGB and NIR (near infrared) wavelength images per individual. One hundred people were studied;therefore 4,800 instances compose the complete database. A Multilayer Perceptron (MLP) was trained to improve the recognition rate in a k-fold cross-validation test with k = 10. Classification results using MLP neural network were obtained using Weka (open source machine learning software).
文摘The temperature change and rate of CO2 change are correlated with a time lag, as reported in a previous paper. The correlation was investigated by calculating a correlation coefficient r of these changes for selected ENSO events in this study. Annual periodical increases and decreases in the CO2 concentration were considered, with a regular pattern of minimum values in August and maximum values in May each year. An increased deviation in CO2 and temperature was found in response to the occurrence of El Niño, but the increase in CO2 lagged behind the change in temperature by 5 months. This pattern was not observed for La Niña events. An increase in global CO2 emissions and a subsequent increase in global temperature proposed by IPCC were not observed, but an increase in global temperature, an increase in soil respiration, and a subsequent increase in global CO2 emissions were noticed. This natural process can be clearly detected during periods of increasing temperature specifically during El Niño events. The results cast strong doubts that anthropogenic CO2 is the cause of global warming.
基金supported by the National Key Research and Development Program of China(No.2022YFA1604703)the National Natural Science Foundation of China(No.12375189)the National Key Research and Development Program of China(No.2021YFA1601300)。
文摘Waveform generation and digitization play essential roles in numerous physics experiments.In traditional distributed systems for large-scale experiments,each frontend node contains an FPGA for data preprocessing,which interfaces with various data converters and exchanges data with a backend central processor.However,the streaming readout architecture has become a new paradigm for several experiments benefiting from advancements in data transmission and computing technologies.This paper proposes a scalable distributed waveform generation and digitization system that utilizes fiber optical connections for data transmission between frontend nodes and a central processor.By utilizing transparent transmission on top of the data link layer,the clock and data ports of the converters in the frontend nodes are directly mapped to the FPGA firmware at the backend.This streaming readout architecture reduces the complexity of frontend development and maintains the data conversion in proximity to the detector.Each frontend node uses a local clock for waveform digitization.To translate the timing information of events in each channel into the system clock domain within the backend central processing FPGA,a novel method is proposed and evaluated using a demonstrator system.
基金supported by the National Key R&D Program of China (No. 2022YFE0204100)the National Natural Science Foundation of China (12205067 and 12375199)the Fundamental Research Funds for the Central Universities (Grant No. HIT.OCEF. 2022036)。
文摘This paper establishes an amplitude modulation heating model, simulating the far-field radiation of ELF/VLF signals generated by modulation heating, as well as the specific location and longitudinal extent of the radiation source. We consider various modulation waveforms and find that square-wave modulation has the highest excitation efficiency for ELF/VLF signals, and that square-wave modulation with a smaller duty cycle(<50%) exhibits higher excitation efficiency for ELF/VLF signals, while the sin^(2)t waveform modulation yields the lowest proportion of harmonic energy in the generated signals. The amplitude of the second harmonic generated by the sin^(2)t waveform is less than one-tenth that of the fundamental frequency, and the energy of higher-frequency harmonics can be negligibly small compared with those of the fundamental wave. It is a challenging task to achieve a balance between enhancing the excitation efficiency of ELF/VLF signals and also suppressing harmonics generated by the modulated heating process. This is because the harmonics are correspondingly enhanced as the excitation efficiency of the signals is increased. However, we find that under conditions of varying effective radiant power and modulation frequency, as long as the modulation waveform is unchanged, the energy ratio between the fundamental frequency signal generated by modulated heating and each harmonic is relatively fixed, with changes only in signal intensity and the location of the radiation source zone. This implies that one can first select modulation waveforms that make the signal less prone to distortion, then increase the effective radiated power to enhance the signal strength, without concern for harmonic interference of the fundamental signal.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20596)the Shenzhen Science and Technology Program(Grant No.GJHZ20220913142605010)the Jinan Lead Researcher Project(Grant No.202333051).
文摘Landslides significantly threaten lives and infrastructure, especially in seismically active regions. This study conducts a probabilistic analysis of seismic landslide runout behavior, leveraging a large-deformation finite-element (LDFE) model that accounts for the three-dimensional (3D) spatial variability and cross-correlation in soil strength — a reflection of natural soils' inherent properties. LDFE model results are validated by comparing them against previous studies, followed by an examination of the effects of univariable, uncorrelated bivariable, and cross-correlated bivariable random fields on landslide runout behavior. The study's findings reveal that integrating variability in both friction angle and cohesion within uncorrelated bivariable random fields markedly influences runout distances when compared with univariable random fields. Moreover, the cross-correlation of soil cohesion and friction angle dramatically affects runout behavior, with positive correlations enlarging and negative correlations reducing runout distances. Transitioning from two-dimensional (2D) to 3D analyses, a more realistic representation of sliding surface, landslide velocity, runout distance and final deposit morphology is achieved. The study highlights that 2D random analyses substantially underestimate the mean value and overestimate the variability of runout distance, underscoring the importance of 3D modeling in accurately predicting landslide behavior. Overall, this work emphasizes the essential role of understanding 3D cross-correlation in soil strength for landslide hazard assessment and mitigation strategies.
基金Projects(61271321,61573253,61401303)supported by the National Natural Science Foundation of ChinaProject(14ZCZDSF00025)supported by Tianjin Key Technology Research and Development Program,China+1 种基金Project(13JCYBJC17500)supported by Tianjin Natural Science Foundation,ChinaProject(20120032110068)supported by Doctoral Fund of Ministry of Education of China
文摘Temporal-spatial cross-correlation analysis of non-stationary wind speed time series plays a crucial role in wind field reconstruction as well as in wind pattern recognition.Firstly,the near-surface wind speed time series recorded at different locations are studied using the detrended fluctuation analysis(DFA),and the corresponding scaling exponents are larger than 1.This indicates that all these wind speed time series have non-stationary characteristics.Secondly,concerning this special feature( i.e.,non-stationarity)of wind signals,a cross-correlation analysis method,namely detrended cross-correlation analysis(DCCA) coefficient,is employed to evaluate the temporal-spatial cross-correlations between non-stationary time series of different anemometer pairs.Finally,experiments on ten wind speed data synchronously collected by the ten anemometers with equidistant arrangement illustrate that the method of DCCA cross-correlation coefficient can accurately analyze full-scale temporal-spatial cross-correlation between non-stationary time series and also can easily identify the seasonal component,while three traditional cross-correlation techniques(i.e.,Pearson coefficient,cross-correlation function,and DCCA method) cannot give us these information directly.
基金supported by the National Science Foundation of China(61561016 61861008+4 种基金 11603041)the Guangxi Natural Science Foundation Project(2018JJA170090)the Innovation Project of Guet Graduate Education(2018YJCX19 2018YJCX31)Guangxi Key Laboratory of Precision Navigation Technology and Application,Guilin University of Electronic Technology(DH201707)
文摘In order to solve the problem of ambiguous acquisition of BOC signals caused by its property of multiple peaks,an unambiguous acquisition algorithm named reconstruction of sub cross-correlation cancellation technique(RSCCT)for BOC(kn,n)signals is proposed.In this paper,the principle of signal decomposition is combined with the traditional acquisition algorithm structure,and then based on the method of reconstructing the correlation function.The method firstly gets the sub-pseudorandom noise(PRN)code by decomposing the local PRN code,then uses BOC(kn,n)and the sub-PRN code cross-correlation to get the sub cross-correlation function.Finally,the correlation peak with a single peak is obtained by reconstructing the sub cross-correlation function so that the ambiguities of BOC acquisition are removed.The simulation shows that RSCCT can completely eliminate the side peaks of BOC(kn,n)group signals while maintaining the narrow correlation of BOC,and its computational complexity is equivalent to sub carrier phase cancellation(SCPC)and autocorrelation side-peak cancellation technique(ASPeCT),and it reduces the computational complexity relative to BPSK-like.For BOC(n,n),the acquisition sensitivity of RSCCT is 3.25 dB,0.81 dB and 0.25 dB higher than binary phase shift keying(BPSK)-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.91,3.0 and 3.7 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.For BOC(2n,n),the acquisition sensitivity of RSCCT is 5.5 dB,1.25 dB and 2.69 dB higher than BPSK-like,SCPC and ASPeCT at the acquisition probability of 90%,respectively.The peak to average power ratio is 1.02,1.68 and 2.12 times higher than ASPeCT,SCPC and BPSK-like at SNR=–20 dB,respectively.
文摘This paper describes the estimation of cloud motion using lag cross-correlation. In order to compute the lag cross correlation, the Bayes Decision method is used first to identify cloud and surface of earth. Then cloud motion vectors are retrieved at a subset of points through multiple applications of a cross-correlation analysis. An objective analysis is used to define displacement at every satellite pixel throughout the domain and smooth the local inconsistencies. Cloud motions are then produced with a backward trajectory technique by using these displacement vectors.
基金supported by the Science Foundation of Jiangsu Province of China (Grant No.BK2011759)
文摘In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject's brain function is healthy or not.
基金financially supported by the Important National Science&Technology Specific Project of China(Grant No.2017ZX05018-005)
文摘Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.
基金The project supported by the National Natural Science Foundation of China
文摘The algorithm of Binary Image Cross-Correlation (BICC) was developed to measure the unsteady flow field. A vortex flow field was used to test the algorithm by numerical simulation. The results show that BICC is an effective algorithm for particle identification from consecutive images, the accurate velocity vector field can be obtained. The real velocity field in a valve chamber was measured by BICC in this study. From the full-field velocity information, the pressure and vorticity fields were also extracted by post-processing. (Edited author abstract) 6 Refs.
基金supported by National Key R&D Program of China(No.2018YFC1503200)National Natural Science Foundation of China(Nos.41674061,41790463 and 41674058)
文摘The amount of seismological data is rapidly increasing with accumulating observational time and increasing number of stations, requiring modern technique to provide adequate computing power. In present study, we proposed a framework to calculate large-scale noise crosscorrelation functions(NCFs) using public cloud service from ALIYUN. The entire computation is factorized into small pieces which are performed parallelly on specified number of virtual servers provided by the cloud. Using data from most seismic stations in China, five NCF databases are built. The results show that, comparing to the time cost using a single server, the entire time can be reduced over two orders of magnitude depending number of evoked virtual servers. This could reduce computation time from months to less than 12 hours. Based on obtained massive NCFs, the global body waves are retrieved through array interferometry and agree well with those from earthquakes. This leads to a solution to process massive seismic dataset within an affordable time and is applicable to other large-scale computing in seismological researches.
文摘In this letter, with the synthesis of usual cross-correlation detecting method andchaotic detecting method, a new detecting system for the weak periodic pulse signal is constituted,in which the two methods can play respective preponderance. Theoretical analyses and simulationstudies have shown that the detecting system is very sensitive to the periodic pulse signal understrong noise background and has exceedingly powerful capability of suppressing complex noise.
基金Project supported by the National Natural Science Foundation of China (Grant No 10472091 and 10332030) and Natural Science Foundation of Shaanxi Province, China (Grant No 2003A03). The author gratefully acknowledges the support of Youth for NPU Teachers Scientific and Technological Innovation Foundation.
文摘This paper shows the Fokker-Planck equation of a dynamical system driven by coloured cross-correlated white noises in the absence and presence of a small external force. Based on the Fokker-Planck equation and the definition of Shannon's information entropy, the time dependence of entropy flux and entropy production can be calculated. The present results can be used to explain the extremal behaviour of time dependence of entropy flux and entropy production in view of the dissipative parameter γ of the system, coloured cross-correlation time τ and coloured cross-correlation strength λ.
基金The project supported by the National Natural Science Foundation of China (59936140 and 59876038)
文摘An improved method that brings enhancement in accuracy for the interrogation of (digital) PIV images is described in this paper. This method is based on cross-correlation with discrete window offset, which makes use of a translation of the second interrogation window and rebuilds it considering rotation and shear. The displacement extracted from PIV images is predicted and corrected by means of an iterative procedure. In addition, the displacement vectors are validated at each intermediate of the iteration process. The present improved cross-correlation method is compared with the conventional one in accuracy by interrogation of synthetic and real (digital) PIV images and the interrogation results are discussed.