Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalize...Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalized Walsh spectrum of multi-output functions and the auto-correlation function of multi-output functions to investigate the Walsh spectral characteristics and the auto-correlation function characteristics of orthormophic permutations, several results are obtained.展开更多
Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture des...Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme： （i） using two-dimensional Gabor filter to extract the texture features of biometric images; （ii） calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and （iii） linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach.展开更多
Most noise suppression algorithms of single channel use the mean of noisy segments to estimate the characteristics of noise spectrum, ignoring the estimation of noise in speech segments. Therefore, when the energy lev...Most noise suppression algorithms of single channel use the mean of noisy segments to estimate the characteristics of noise spectrum, ignoring the estimation of noise in speech segments. Therefore, when the energy level of noise varies with the time, the performance of removing noise will be degraded. To solve this problem, a speech enhancement approach based on dynamic noise estimation within correlation domain was proposed. This method exploits the characteristics that noise energy mainly concentrates on 0 th order correlation coefficients, signal is auto correlated but signal and noise, noise and noise are uncorrelated, then estimates and decomposes the noise, thus helps to solve the above mentioned problem. The results of recognition experiments on speech signals of 15 Chinese cities’ names corrupted by noise of exhibition hall shows, this approach is better than SS (Spectral Subtraction) method, adapts better to the variances of energy levels of speech signal corrupted by noise, has some practicability to improve the robustness of recognition systems under noisy environment.展开更多
In this paper, a sufficient and necessary condition of quick trickle permutations is given from the point of inverse permutations. The bridge is built between quick trickle permutations and m-value logic functions. By...In this paper, a sufficient and necessary condition of quick trickle permutations is given from the point of inverse permutations. The bridge is built between quick trickle permutations and m-value logic functions. By the methods of the Chrestenson spectrum of m-value logic functions and the auto-correlation function of m-value logic functions to investigate the Chrestenson spectral characteristics and the auto-correlation function charac- teristics of inverse permutations of quick trickle permutations, a determinant arithmetic of quick trickle permutations is given. Using the results, it becomes easy to judge that a permutation is a quick trickle permutation or not by using computer. This gives a new pathway to study constructions and enumerations of quick trickle permutations.展开更多
In recent years,the time-frequency overlapping multi-carrier signal has been a novel and valuable topic in blind signal processing,especially in the non-cooperative receiving field.But there is little related research...In recent years,the time-frequency overlapping multi-carrier signal has been a novel and valuable topic in blind signal processing,especially in the non-cooperative receiving field.But there is little related research in public published papers.This paper proposes two timing estimation algorithms,which are non-data-aided and based on the cyclic auto-correlation function.In order to evaluate the performance of the proposed algorithms,the theoretical bound of the timing estimation is derived.According to the analyses and simulation results,the effectiveness of the proposed algorithms has been demonstrated.It shows that MethodⅠhas better performance than MethodⅡ.However,MethodⅡdoes not need prior information,so it has a wider range of applications.展开更多
The fingerspelling recognition by hand shape is an important step for developing a human-computer interaction system. A method of fingerspelling recognition by hand shape using HLAC （higher-order local auto-correlat...The fingerspelling recognition by hand shape is an important step for developing a human-computer interaction system. A method of fingerspelling recognition by hand shape using HLAC （higher-order local auto-correlation） features is proposed. Furthermore, in order to use HLAC features more effectively, the use of image processing techniques： reducing an image resolution, dividing an image, and image pre-processing techniques, is also proposed. The experimental results show that the proposed method is promising.展开更多
Bridges are omnipresent in every society and they affect its human, social, ecological, economical and cultural aspects. This is why a durable and safe usage of bridges is an imperative goal of structural management. ...Bridges are omnipresent in every society and they affect its human, social, ecological, economical and cultural aspects. This is why a durable and safe usage of bridges is an imperative goal of structural management. Measurement and monitoring have an essential role in structural management. The benefits of the information obtained by monitoring are apparent in several domains. In deformation analysis, the functional relationship between the acting forces and the resulting deformations should be established. If time depending observations are given, a regression could be used as a functional model. In case of stochastic model uncorrelated observations with identical variance are assumed. Due to the high sampling rate, a small time difference arises between two observations. Thus the assumed stochastic model is not suitable. The calculation has to be effected by means of auto-correlated observations. This paper investigates an integrated monitoring system for the estimation of the deformation (i.e., static, quasi-static) behavior of bridges from total station observations and studies the effect of autocorrelation technique on the accuracy of the estimated parameters and variances. The results have shown that autocorrelation technique is reduced the standard deviation of X&Y-direction about 6.7% to 29.4% and 6.5% to 15.5% of the original value, respectively, but the situation was differ in Z direction;the standard deviation in vertical component Z was increased.展开更多
Infrared spectroscopy analysis has found widespread applications in various fields due to advancements in technology and industry convergence.To improve the quality and reliability of infrared spectroscopy signals,dec...Infrared spectroscopy analysis has found widespread applications in various fields due to advancements in technology and industry convergence.To improve the quality and reliability of infrared spectroscopy signals,deconvolution is a crucial preprocessing step.Inspired by the transformer model,we propose an Auto-correlation Multi-head attention Transformer(AMTrans)for infrared spectrum sequence deconvolution.The auto-correlation attention model improves the scaled dot-product attention in the transformer.It utilizes attention mechanism for feature extraction and implements attention computation using the auto-correlation function.The auto-correlation attention model is used to exploit the inherent sequence nature of spectral data and to effectively recovery spectra by capturing auto-correlation patterns in the sequence.The proposed model is trained using supervised learning and demonstrates promising results in infrared spectroscopic restoration.By comparing the experiments with other deconvolution techniques,the experimental results show that the method has excellent deconvolution performance and can effectively recover the texture details of the infrared spectrum.展开更多
Autocorrelations exist in real production extensively,and special statistical tools are needed for process monitoring.Residual charts based on autoregressive integrated moving average(ARIMA)models are typically used.H...Autocorrelations exist in real production extensively,and special statistical tools are needed for process monitoring.Residual charts based on autoregressive integrated moving average(ARIMA)models are typically used.However,ARIMA models need a quite amount of experience,which sometimes causes inconveniences in the implementation.With a good performance under less experience or even none,hidden Markov models(HMMs)were proposed.Since ARIMA models have many different performances in positive and negative autocorrelations,it is interesting and essential to study how HMMs affect the performances of residual charts in opposite autocorrelations,which has not been studied yet.Therefore,we extend HMMs to negatively auto-correlated observations.The cross-validation method is used to select the relatively optimal state number.The experiment results show that HMMs are more stable than Auto-Regressive of order one(AR(1)models)in both cases of positive and negative autocorrelations.For detecting abnormalities,the performance of HMMs approach is much better than AR(1)models under positive autocorrelations while under negative autocorrelations both methods have similar performances.展开更多
Machine learning methods dealing with the spatial auto-correlation of the response variable have garnered significant attention in the context of spatial prediction.Nonetheless,under these methods,the relationship bet...Machine learning methods dealing with the spatial auto-correlation of the response variable have garnered significant attention in the context of spatial prediction.Nonetheless,under these methods,the relationship between the response variable and explanatory variables is assumed to be homogeneous throughout the entire study area.This assumption,known as spatial stationarity,is very questionable in real-world situations due to the influence of contextual factors.Therefore,allowing the relationship between the target variable and predictor variables to vary spatially within the study region is more reasonable.However,existing machine learning techniques accounting for the spatially varying relationship between the dependent variable and the predictor variables do not capture the spatial auto-correlation of the dependent variable itself.Moreover,under these techniques,local machine learning models are effectively built using only fewer observations,which can lead to well-known issues such as over-fitting and the curse of dimensionality.This paper introduces a novel geostatistical machine learning approach where both the spatial auto-correlation of the response variable and the spatial non-stationarity of the regression relationship between the response and predictor variables are explicitly considered.The basic idea consists of relying on the local stationarity assumption to build a collection of local machine learning models while leveraging on the local spatial auto-correlation of the response variable to locally augment the training dataset.The proposed method’s effectiveness is showcased via experiments conducted on synthetic spatial data with known characteristics as well as real-world spatial data.In the synthetic(resp.real)case study,the proposed method’s predictive accuracy,as indicated by the Root Mean Square Error(RMSE)on the test set,is 17%(resp.7%)better than that of popular machine learning methods dealing with the response variable’s spatial auto-correlation.Additionally,this method is not only valuable for spatial prediction but also offers a deeper understanding of how the relationship between the target and predictor variables varies across space,and it can even be used to investigate the local significance of predictor variables.展开更多
The amino acid composition and the biased auto-correlation function are considered as features, BP neural network algorithm is used to synthesize these features. The prediction accuracy of this method is verified by u...The amino acid composition and the biased auto-correlation function are considered as features, BP neural network algorithm is used to synthesize these features. The prediction accuracy of this method is verified by using the independent non-homologous protein database. It is shown that the average absolute errors for resubstitution test are 0.070 and 0.068 with the standard deviations 0.049 and 0.047 for the prediction of the content of α-helix and β-sheet respectively. For cross-validation test, the average absolute errors are 0.075 and 0.070 with the standard deviations 0.050 and 0.049 for the prediction of the content of α-helix and β-sheet respectively. Compared with the other methods currently available, the BP neural network method combined with the amino acid composition and the biased auto-correlation function features can effectively improve the prediction accuracy.展开更多
The purpose of this paper is to establish sev eral identities containing Gaussian binomial coefficient. These results generali ze several Mercier's results. Key words:Gaussian binomial coefficient; identity; the ...The purpose of this paper is to establish sev eral identities containing Gaussian binomial coefficient. These results generali ze several Mercier's results. Key words:Gaussian binomial coefficient; identity; the functio n A(T,T 2,...,T n)culating eige nvalues of auto-correlation matrix of the physical control force of actuators. T he optimization algorithm calculating the optimal actuator placement is then put forward via the minimization of an energy criterion, which is chosen as the con trol index. Numerical examples show the effectiveness of the proposed method.展开更多
Molecular dynamics calculation of UO2 in a wide temperature range are presented and dis- cussed. The calculated lattice parameters, mean square displacements, and dynamic prop- erty of phonon-level density of the velo...Molecular dynamics calculation of UO2 in a wide temperature range are presented and dis- cussed. The calculated lattice parameters, mean square displacements, and dynamic prop- erty of phonon-level density of the velocity auto-correlation functions for UO2 are provided. The Morelon potential and the Basak potential are employed. It confirms that the cal- culated lattice parameters using the Basak potential are in nearly perfect agreement with the reported values. The models successfully predict mean square displacement and Bredig transition. Furthermore, the phonon-level density of uranium dioxide are discussed. The intensity of phonon-level density increases with temperature, and the properties of UO2 are characterized by large thermal vibrations rather than extensive disorder.展开更多
The parallel spectral-domain optical coherence tomography（PSDOCT） is described for highspeed optical coherence tomography（OCT） without lateral scanning. In this setup, the self-elimination of auto-correlation（AC...The parallel spectral-domain optical coherence tomography（PSDOCT） is described for highspeed optical coherence tomography（OCT） without lateral scanning. In this setup, the self-elimination of auto-correlation（AC） interference algorithm was used for eradicating the AC interference and ghost images. However, when performed in free space OCT, this algorithm still generated a weak DC component. The algorithm was improved by adding the background intensity part to compensate for the mutual interference between object and reference arms. The results demonstrate that the DC component can be eradicated. Compared with conventional QCT and complex Fourier-domain optical coherence to- mography, the advantages of PSDOCT with the improved algorithm in free space are that it has no moving parts to generate consecutive phase shift, the structure of the object can be reconstructed immediately and automatically, and the speed is approximately 16 times faster than those of the other two in the same case.展开更多
The sea-ice concentration in the Northern Hemisphere, 500 hPa height, sea-level pressure and 1000-500 hPa thickness of monthly mean data are examined for the period 1953-1989, with emphasis on the winter season.Relati...The sea-ice concentration in the Northern Hemisphere, 500 hPa height, sea-level pressure and 1000-500 hPa thickness of monthly mean data are examined for the period 1953-1989, with emphasis on the winter season.Relationships between large-scale patterns of atmospheric variability and sea-ice variability are investigated, making use of the correlation method. The analysis is conducted for the Atlantic sectors. In agreement with earlier studies based upon monthly mean data on sea-ice concentration, the strongest sea-ice pattern is composed of a dipole with opposing centers of action in the Davis Straits / Labrador Sea region and the Greenland and Barents Seas. Its temporal variability is strongly coupled to the atmospheric North Atlantic Oscillation (NAO). The relationship between the two patterns is strongest with the atmosphere leading the ocean. The polarity of the NAO is associated with Greenland blocking episodes, during which the influence of the atmosphere is strong enough to temporarily halt the climatological mean advance of the ice edge in some regions and substantially accelerate it in others.The relationships between the fields are indicative of local forcing of sea-ice in most regions, with wind stress and thermodynamic fluxes at the air-sea interface both contributing.展开更多
On the basis of spatial-temporal perspective,by using the data of farmers' net income per capita from 1996 to 2007 in counties of Guangxi coupled with the global and local spatial auto-correlation analysis of ESDA...On the basis of spatial-temporal perspective,by using the data of farmers' net income per capita from 1996 to 2007 in counties of Guangxi coupled with the global and local spatial auto-correlation analysis of ESDA and GIS technology,we conduct the empirical research on the rural economic developmental disparity of counties in Guangxi and the evolving characteristics of local spatial heterogeneity.The results show that the rural economic developmental disparity of counties in Guangxi from 1996 to 2007 varies infinitesimally on the whole,and the regions with similar rural economic developmental level have spatial concentrated distribution.Based on these,the local MORAN'S I scatter diagram and LISA concentration diagram are drawn.In comparison with the traditional analytical method,the spatial analytical method of ESDA-GIS can explain the problem of spatial heterogeneity of rural economic development clearly,and have direct visual effect.展开更多
Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through...Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements（May 25 2007-2008）, statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, ＂Weibull＂ had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.展开更多
Source-generated energy in seismic vibrator records high frequency harmonic behavior. Conventional vibrator-earth coupling model was set up on the linear system. Some assumptions in the application of linear theory to...Source-generated energy in seismic vibrator records high frequency harmonic behavior. Conventional vibrator-earth coupling model was set up on the linear system. Some assumptions in the application of linear theory to the vibrator problem play an insignificant role in the overall coupling structure. Obviously, non-linear behaviors can be modeled using a “hard-spring” form of the Duffing equation. Model dedicates that a qualitatively similar harmonic component is present for a broad range of possible mathematical descriptions. After some qualitative analysis about the non-linear system, some conclusion can be drawn. Firstly, The design of the vibrator weight should be abided by two points as followed: In order to avoid decoupling for the vibrator to the earth, the weight should be greater than the peak of the driving force amplitude as to keep the resultant force pointing to the earth’s core. On the other hand, for the limited energy output, the vibrator overweight may damage the system high-frequency ability.Secondly, as the driving force frequency approaching to the ground hard-spring inherent frequency, the energy transmission was found to climb its peak from the system energy absorbed curve. At last, due to the non-linear coupling model system, its load curve would come into unstable frequency range, which might limit the application of the Vibroseis conventional sweeping pattern-linear sweep. A new sweeping pattern was listed: the driving signal was the pseudo-random sequence modulated by a fixed frequency cosine signal satisfying with the exploration precision and absorbing efficiency. The synthesized signal was ready to be realized by the electromagnetic driven system. Even the side-lobes noise of its auto-correlation function was restrained well. The theory coming from the Vibrator-earth coupling model was applied to the design of the Portable High-frequency Vibrator System (PHVS), and the good result was obtained. By the analysis of the vibrator base plate signal, the model was proved to be true. The exploration research on PHVS made a first step on its following optimal design.展开更多
Considering that channel estimation can play a crucial role in coherent detection of the information symbols in each data block, a blind channel estimation approach is proposed for redundant precoded orthogonal freque...Considering that channel estimation can play a crucial role in coherent detection of the information symbols in each data block, a blind channel estimation approach is proposed for redundant precoded orthogonal frequency-division multiplexing （OFDM） systems. A redundant linear frequency-domain precoder is applied to each pair of blocks before they enter the OFDM system. Because of the introduced structure, the frequency-selective channel can be identified at the receiver based on autocorrelation operations, singular value decomposition （SVD）, and by resolving the scalar ambiguity. The proposed channel estimation method has low computational complexity and requires no prior statistical information on channel or noise. And the proposed blind method has high spectral efficiency owing to exploiting no training sequence. Computer simulations confirm that this proposed blind channel estimation method can identify the frequency-selective channels perfectly and obtain a good performance.展开更多
Among cancers, lung cancer is the most common cause of death in China. For the prevention and control of lung cancer, it is necessary to investigate the spatial and temporal distribution of lung cancer mortality, as w...Among cancers, lung cancer is the most common cause of death in China. For the prevention and control of lung cancer, it is necessary to investigate the spatial and temporal distribution of lung cancer mortality, as well as the changes in the trend and the affecting mechanism. Based on statistics and auto-correlation analysis, this paper studied the spatial and temporal distribution of lung cancer mortality in Yuhui District, Bengbu, Huaihe River Basin, from 2017 to 2020. In addition, Spearman’s Rank Correlation Assessment Model and Geographic Detector Model were used to examine the relationship between environmental factors and lung cancer mortality to identify impact factors and their mechanisms. The findings indicated that: 1) from the characteristics of temporal distribution, the number of lung cancer deaths exhibited a linear growth tendency, with the highest mortality in winter;2) from the characteristics of spatial distribution, lung cancer mortality showed a strong spatial agglomeration form, concentrating on two clustering areas, located in the old city and the central city of Bengbu, near the Huaihe River;3) from the point of view of the whole research area, there were 15 impact factors with significant correlation in the built and natural environment factors. The significant impacting factors in the built environment included land use, road traffic, spatial form and blue-green space, which could indirectly affect lung cancer mortality, while air pollution and temperature constituted the significant impacting factors in the natural environment;4) the influence of screened environmental factors on lung cancer mortality was different. Spatial stratified heterogeneity assessment, the interaction among environmental factors demonstrated statistical significance, it was found that the interaction between environmental factors in pairs had a significant enhancement effect on lung cancer mortality. To some extent, urban planning and policies could reduce lung cancer mortality.展开更多
基金Supported by State Key Laboratory of InformationSecurity Opening Foundation(01-02) .
文摘Orthomorphic permutations have good characteristics in cryptosystems. In this paper, by using of knowledge about relation between orthomorphic permutations and multi-output functions, and conceptions of the generalized Walsh spectrum of multi-output functions and the auto-correlation function of multi-output functions to investigate the Walsh spectral characteristics and the auto-correlation function characteristics of orthormophic permutations, several results are obtained.
基金supported by the National Natural Science Foundation of China(Grant Nos.61262040,61271341,81360230,and 61271007)the Applied Basic Research Projects of Yunnan Province,China(Grant No.KKSY201203062)
文摘Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme： （i） using two-dimensional Gabor filter to extract the texture features of biometric images; （ii） calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and （iii） linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach.
文摘Most noise suppression algorithms of single channel use the mean of noisy segments to estimate the characteristics of noise spectrum, ignoring the estimation of noise in speech segments. Therefore, when the energy level of noise varies with the time, the performance of removing noise will be degraded. To solve this problem, a speech enhancement approach based on dynamic noise estimation within correlation domain was proposed. This method exploits the characteristics that noise energy mainly concentrates on 0 th order correlation coefficients, signal is auto correlated but signal and noise, noise and noise are uncorrelated, then estimates and decomposes the noise, thus helps to solve the above mentioned problem. The results of recognition experiments on speech signals of 15 Chinese cities’ names corrupted by noise of exhibition hall shows, this approach is better than SS (Spectral Subtraction) method, adapts better to the variances of energy levels of speech signal corrupted by noise, has some practicability to improve the robustness of recognition systems under noisy environment.
基金the Opening Foundation of State Key Labo-ratory of Information Security (20050102)
文摘In this paper, a sufficient and necessary condition of quick trickle permutations is given from the point of inverse permutations. The bridge is built between quick trickle permutations and m-value logic functions. By the methods of the Chrestenson spectrum of m-value logic functions and the auto-correlation function of m-value logic functions to investigate the Chrestenson spectral characteristics and the auto-correlation function charac- teristics of inverse permutations of quick trickle permutations, a determinant arithmetic of quick trickle permutations is given. Using the results, it becomes easy to judge that a permutation is a quick trickle permutation or not by using computer. This gives a new pathway to study constructions and enumerations of quick trickle permutations.
基金supported by the National Natural Science Foundation of China under Grant No. 61501084。
文摘In recent years,the time-frequency overlapping multi-carrier signal has been a novel and valuable topic in blind signal processing,especially in the non-cooperative receiving field.But there is little related research in public published papers.This paper proposes two timing estimation algorithms,which are non-data-aided and based on the cyclic auto-correlation function.In order to evaluate the performance of the proposed algorithms,the theoretical bound of the timing estimation is derived.According to the analyses and simulation results,the effectiveness of the proposed algorithms has been demonstrated.It shows that MethodⅠhas better performance than MethodⅡ.However,MethodⅡdoes not need prior information,so it has a wider range of applications.
文摘The fingerspelling recognition by hand shape is an important step for developing a human-computer interaction system. A method of fingerspelling recognition by hand shape using HLAC （higher-order local auto-correlation） features is proposed. Furthermore, in order to use HLAC features more effectively, the use of image processing techniques： reducing an image resolution, dividing an image, and image pre-processing techniques, is also proposed. The experimental results show that the proposed method is promising.
文摘Bridges are omnipresent in every society and they affect its human, social, ecological, economical and cultural aspects. This is why a durable and safe usage of bridges is an imperative goal of structural management. Measurement and monitoring have an essential role in structural management. The benefits of the information obtained by monitoring are apparent in several domains. In deformation analysis, the functional relationship between the acting forces and the resulting deformations should be established. If time depending observations are given, a regression could be used as a functional model. In case of stochastic model uncorrelated observations with identical variance are assumed. Due to the high sampling rate, a small time difference arises between two observations. Thus the assumed stochastic model is not suitable. The calculation has to be effected by means of auto-correlated observations. This paper investigates an integrated monitoring system for the estimation of the deformation (i.e., static, quasi-static) behavior of bridges from total station observations and studies the effect of autocorrelation technique on the accuracy of the estimated parameters and variances. The results have shown that autocorrelation technique is reduced the standard deviation of X&Y-direction about 6.7% to 29.4% and 6.5% to 15.5% of the original value, respectively, but the situation was differ in Z direction;the standard deviation in vertical component Z was increased.
基金supported by the National Natural Science Foundation of China(No.62072256).
文摘Infrared spectroscopy analysis has found widespread applications in various fields due to advancements in technology and industry convergence.To improve the quality and reliability of infrared spectroscopy signals,deconvolution is a crucial preprocessing step.Inspired by the transformer model,we propose an Auto-correlation Multi-head attention Transformer(AMTrans)for infrared spectrum sequence deconvolution.The auto-correlation attention model improves the scaled dot-product attention in the transformer.It utilizes attention mechanism for feature extraction and implements attention computation using the auto-correlation function.The auto-correlation attention model is used to exploit the inherent sequence nature of spectral data and to effectively recovery spectra by capturing auto-correlation patterns in the sequence.The proposed model is trained using supervised learning and demonstrates promising results in infrared spectroscopic restoration.By comparing the experiments with other deconvolution techniques,the experimental results show that the method has excellent deconvolution performance and can effectively recover the texture details of the infrared spectrum.
基金the National Natural Science Foundation of China(No.71701098)Natural Science Foundation of Jiangsu Province(No.BK20160940)+1 种基金Humanities and Social Sciences Youth Fund of Chinese Ministry of Education(No.17YJC630070)Philosophy and Social Sciences Fund of Colleges and Universities in Jiangsu Province(No.2017SJB0105)
文摘Autocorrelations exist in real production extensively,and special statistical tools are needed for process monitoring.Residual charts based on autoregressive integrated moving average(ARIMA)models are typically used.However,ARIMA models need a quite amount of experience,which sometimes causes inconveniences in the implementation.With a good performance under less experience or even none,hidden Markov models(HMMs)were proposed.Since ARIMA models have many different performances in positive and negative autocorrelations,it is interesting and essential to study how HMMs affect the performances of residual charts in opposite autocorrelations,which has not been studied yet.Therefore,we extend HMMs to negatively auto-correlated observations.The cross-validation method is used to select the relatively optimal state number.The experiment results show that HMMs are more stable than Auto-Regressive of order one(AR(1)models)in both cases of positive and negative autocorrelations.For detecting abnormalities,the performance of HMMs approach is much better than AR(1)models under positive autocorrelations while under negative autocorrelations both methods have similar performances.
文摘Machine learning methods dealing with the spatial auto-correlation of the response variable have garnered significant attention in the context of spatial prediction.Nonetheless,under these methods,the relationship between the response variable and explanatory variables is assumed to be homogeneous throughout the entire study area.This assumption,known as spatial stationarity,is very questionable in real-world situations due to the influence of contextual factors.Therefore,allowing the relationship between the target variable and predictor variables to vary spatially within the study region is more reasonable.However,existing machine learning techniques accounting for the spatially varying relationship between the dependent variable and the predictor variables do not capture the spatial auto-correlation of the dependent variable itself.Moreover,under these techniques,local machine learning models are effectively built using only fewer observations,which can lead to well-known issues such as over-fitting and the curse of dimensionality.This paper introduces a novel geostatistical machine learning approach where both the spatial auto-correlation of the response variable and the spatial non-stationarity of the regression relationship between the response and predictor variables are explicitly considered.The basic idea consists of relying on the local stationarity assumption to build a collection of local machine learning models while leveraging on the local spatial auto-correlation of the response variable to locally augment the training dataset.The proposed method’s effectiveness is showcased via experiments conducted on synthetic spatial data with known characteristics as well as real-world spatial data.In the synthetic(resp.real)case study,the proposed method’s predictive accuracy,as indicated by the Root Mean Square Error(RMSE)on the test set,is 17%(resp.7%)better than that of popular machine learning methods dealing with the response variable’s spatial auto-correlation.Additionally,this method is not only valuable for spatial prediction but also offers a deeper understanding of how the relationship between the target and predictor variables varies across space,and it can even be used to investigate the local significance of predictor variables.
文摘The amino acid composition and the biased auto-correlation function are considered as features, BP neural network algorithm is used to synthesize these features. The prediction accuracy of this method is verified by using the independent non-homologous protein database. It is shown that the average absolute errors for resubstitution test are 0.070 and 0.068 with the standard deviations 0.049 and 0.047 for the prediction of the content of α-helix and β-sheet respectively. For cross-validation test, the average absolute errors are 0.075 and 0.070 with the standard deviations 0.050 and 0.049 for the prediction of the content of α-helix and β-sheet respectively. Compared with the other methods currently available, the BP neural network method combined with the amino acid composition and the biased auto-correlation function features can effectively improve the prediction accuracy.
文摘The purpose of this paper is to establish sev eral identities containing Gaussian binomial coefficient. These results generali ze several Mercier's results. Key words:Gaussian binomial coefficient; identity; the functio n A(T,T 2,...,T n)culating eige nvalues of auto-correlation matrix of the physical control force of actuators. T he optimization algorithm calculating the optimal actuator placement is then put forward via the minimization of an energy criterion, which is chosen as the con trol index. Numerical examples show the effectiveness of the proposed method.
文摘Molecular dynamics calculation of UO2 in a wide temperature range are presented and dis- cussed. The calculated lattice parameters, mean square displacements, and dynamic prop- erty of phonon-level density of the velocity auto-correlation functions for UO2 are provided. The Morelon potential and the Basak potential are employed. It confirms that the cal- culated lattice parameters using the Basak potential are in nearly perfect agreement with the reported values. The models successfully predict mean square displacement and Bredig transition. Furthermore, the phonon-level density of uranium dioxide are discussed. The intensity of phonon-level density increases with temperature, and the properties of UO2 are characterized by large thermal vibrations rather than extensive disorder.
文摘The parallel spectral-domain optical coherence tomography（PSDOCT） is described for highspeed optical coherence tomography（OCT） without lateral scanning. In this setup, the self-elimination of auto-correlation（AC） interference algorithm was used for eradicating the AC interference and ghost images. However, when performed in free space OCT, this algorithm still generated a weak DC component. The algorithm was improved by adding the background intensity part to compensate for the mutual interference between object and reference arms. The results demonstrate that the DC component can be eradicated. Compared with conventional QCT and complex Fourier-domain optical coherence to- mography, the advantages of PSDOCT with the improved algorithm in free space are that it has no moving parts to generate consecutive phase shift, the structure of the object can be reconstructed immediately and automatically, and the speed is approximately 16 times faster than those of the other two in the same case.
文摘The sea-ice concentration in the Northern Hemisphere, 500 hPa height, sea-level pressure and 1000-500 hPa thickness of monthly mean data are examined for the period 1953-1989, with emphasis on the winter season.Relationships between large-scale patterns of atmospheric variability and sea-ice variability are investigated, making use of the correlation method. The analysis is conducted for the Atlantic sectors. In agreement with earlier studies based upon monthly mean data on sea-ice concentration, the strongest sea-ice pattern is composed of a dipole with opposing centers of action in the Davis Straits / Labrador Sea region and the Greenland and Barents Seas. Its temporal variability is strongly coupled to the atmospheric North Atlantic Oscillation (NAO). The relationship between the two patterns is strongest with the atmosphere leading the ocean. The polarity of the NAO is associated with Greenland blocking episodes, during which the influence of the atmosphere is strong enough to temporarily halt the climatological mean advance of the ice edge in some regions and substantially accelerate it in others.The relationships between the fields are indicative of local forcing of sea-ice in most regions, with wind stress and thermodynamic fluxes at the air-sea interface both contributing.
文摘On the basis of spatial-temporal perspective,by using the data of farmers' net income per capita from 1996 to 2007 in counties of Guangxi coupled with the global and local spatial auto-correlation analysis of ESDA and GIS technology,we conduct the empirical research on the rural economic developmental disparity of counties in Guangxi and the evolving characteristics of local spatial heterogeneity.The results show that the rural economic developmental disparity of counties in Guangxi from 1996 to 2007 varies infinitesimally on the whole,and the regions with similar rural economic developmental level have spatial concentrated distribution.Based on these,the local MORAN'S I scatter diagram and LISA concentration diagram are drawn.In comparison with the traditional analytical method,the spatial analytical method of ESDA-GIS can explain the problem of spatial heterogeneity of rural economic development clearly,and have direct visual effect.
文摘Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements（May 25 2007-2008）, statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, ＂Weibull＂ had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.
文摘Source-generated energy in seismic vibrator records high frequency harmonic behavior. Conventional vibrator-earth coupling model was set up on the linear system. Some assumptions in the application of linear theory to the vibrator problem play an insignificant role in the overall coupling structure. Obviously, non-linear behaviors can be modeled using a “hard-spring” form of the Duffing equation. Model dedicates that a qualitatively similar harmonic component is present for a broad range of possible mathematical descriptions. After some qualitative analysis about the non-linear system, some conclusion can be drawn. Firstly, The design of the vibrator weight should be abided by two points as followed: In order to avoid decoupling for the vibrator to the earth, the weight should be greater than the peak of the driving force amplitude as to keep the resultant force pointing to the earth’s core. On the other hand, for the limited energy output, the vibrator overweight may damage the system high-frequency ability.Secondly, as the driving force frequency approaching to the ground hard-spring inherent frequency, the energy transmission was found to climb its peak from the system energy absorbed curve. At last, due to the non-linear coupling model system, its load curve would come into unstable frequency range, which might limit the application of the Vibroseis conventional sweeping pattern-linear sweep. A new sweeping pattern was listed: the driving signal was the pseudo-random sequence modulated by a fixed frequency cosine signal satisfying with the exploration precision and absorbing efficiency. The synthesized signal was ready to be realized by the electromagnetic driven system. Even the side-lobes noise of its auto-correlation function was restrained well. The theory coming from the Vibrator-earth coupling model was applied to the design of the Portable High-frequency Vibrator System (PHVS), and the good result was obtained. By the analysis of the vibrator base plate signal, the model was proved to be true. The exploration research on PHVS made a first step on its following optimal design.
基金This project was supported by the National Natural Science Foundation of China (60572157)National Hi-Tech Research and Development Program (863) of China (2003AA123310).
文摘Considering that channel estimation can play a crucial role in coherent detection of the information symbols in each data block, a blind channel estimation approach is proposed for redundant precoded orthogonal frequency-division multiplexing （OFDM） systems. A redundant linear frequency-domain precoder is applied to each pair of blocks before they enter the OFDM system. Because of the introduced structure, the frequency-selective channel can be identified at the receiver based on autocorrelation operations, singular value decomposition （SVD）, and by resolving the scalar ambiguity. The proposed channel estimation method has low computational complexity and requires no prior statistical information on channel or noise. And the proposed blind method has high spectral efficiency owing to exploiting no training sequence. Computer simulations confirm that this proposed blind channel estimation method can identify the frequency-selective channels perfectly and obtain a good performance.
基金Under the auspices of Natural Science Foundation of Anhui Province (No. 2008085ME160)Provincial Natural Science Research Projects in Anhui Province-Postgraduate Projects (No. YJS20210500)。
文摘Among cancers, lung cancer is the most common cause of death in China. For the prevention and control of lung cancer, it is necessary to investigate the spatial and temporal distribution of lung cancer mortality, as well as the changes in the trend and the affecting mechanism. Based on statistics and auto-correlation analysis, this paper studied the spatial and temporal distribution of lung cancer mortality in Yuhui District, Bengbu, Huaihe River Basin, from 2017 to 2020. In addition, Spearman’s Rank Correlation Assessment Model and Geographic Detector Model were used to examine the relationship between environmental factors and lung cancer mortality to identify impact factors and their mechanisms. The findings indicated that: 1) from the characteristics of temporal distribution, the number of lung cancer deaths exhibited a linear growth tendency, with the highest mortality in winter;2) from the characteristics of spatial distribution, lung cancer mortality showed a strong spatial agglomeration form, concentrating on two clustering areas, located in the old city and the central city of Bengbu, near the Huaihe River;3) from the point of view of the whole research area, there were 15 impact factors with significant correlation in the built and natural environment factors. The significant impacting factors in the built environment included land use, road traffic, spatial form and blue-green space, which could indirectly affect lung cancer mortality, while air pollution and temperature constituted the significant impacting factors in the natural environment;4) the influence of screened environmental factors on lung cancer mortality was different. Spatial stratified heterogeneity assessment, the interaction among environmental factors demonstrated statistical significance, it was found that the interaction between environmental factors in pairs had a significant enhancement effect on lung cancer mortality. To some extent, urban planning and policies could reduce lung cancer mortality.
