The relations between Gaussian function and Γ function is revealed first at one dimensional situation. Then, the Fourier transformation of n dimensional Gaussian function is deduced by a lemma. Following th...The relations between Gaussian function and Γ function is revealed first at one dimensional situation. Then, the Fourier transformation of n dimensional Gaussian function is deduced by a lemma. Following the train of thought in one dimensional situation, the relation between n dimensional Gaussian function and Γ function is given. By these, the possibility of arbitrary derivative of an n dimensional Gaussian function being a mother wavelet is indicated. The result will take some enlightening role in exploring the internal relations between Gaussian function and Γ function as well as in finding high dimensional mother wavelets.展开更多
The numerical simulation of the fluid flow and the flexible rod(s)interaction is more complicated and has lower efficiency due to the high computational cost.In this paper,a semi-resolved model coupling the computatio...The numerical simulation of the fluid flow and the flexible rod(s)interaction is more complicated and has lower efficiency due to the high computational cost.In this paper,a semi-resolved model coupling the computational fluid dynamics and the flexible rod dynamics is proposed using a two-way domain expansion method.The gov-erning equations of the flexible rod dynamics are discretized and solved by the finite element method,and the fluid flow is simulated by the finite volume method.The interaction between fluids and solid rods is modeled by introducing body force terms into the momentum equations.Referred to the traditional semi-resolved numerical model,an anisotropic Gaussian kernel function method is proposed to specify the interactive forces between flu-ids and solid bodies for non-circle rod cross-sections.A benchmark of the flow passing around a single flexible plate with a rectangular cross-section is used to validate the algorithm.Focused on the engineering applications,a test case of a finite patch of cylinders is implemented to validate the accuracy and efficiency of the coupled model.展开更多
The performance of two models,Jam and Baig,based on the modified version of Gaussian distribution function in estimating the daily total of global solar radiation and its distribution through the hours of the day from...The performance of two models,Jam and Baig,based on the modified version of Gaussian distribution function in estimating the daily total of global solar radiation and its distribution through the hours of the day from sunrise to sunset al any clear day is evaluated with our own measured data in the period from June 1992 to May 1993 in Qena Egypt The results show a high relative deviation of calculated values from measured ones,especially for Jain model,in the most hours of the day,except for those near to local noon.This misfit behavior is quite obvious in the early morning and late afternoon A new approach has been proposed in this paper to estimate the daily and hourly global solar radiation This model performs with very high accuracy on the recorded data in our region.The validity of this approach was verified with new measurements in some clear days in June and August 1994.The resultant very low relative deviation of the calculated values of global solar radiation from the measured ones confirms the high performance of the approach proposed in this work展开更多
Most existing algorithms for the underdetermined blind source separation(UBSS) problem are two-stage algorithm, i.e., mixing parameters estimation and sources estimation. In the mixing parameters estimation, the previ...Most existing algorithms for the underdetermined blind source separation(UBSS) problem are two-stage algorithm, i.e., mixing parameters estimation and sources estimation. In the mixing parameters estimation, the previously proposed traditional clustering algorithms are sensitive to the initializations of the mixing parameters. To reduce the sensitiveness to the initialization, we propose a new algorithm for the UBSS problem based on anechoic speech mixtures by employing the visual information, i.e., the interaural time difference(ITD) and the interaural level difference(ILD), as the initializations of the mixing parameters. In our algorithm, the video signals are utilized to estimate the distances between microphones and sources, and then the estimations of the ITD and ILD can be obtained. With the sparsity assumption in the time-frequency domain, the Gaussian potential function algorithm is utilized to estimate the mixing parameters by using the ITDs and ILDs as the initializations of the mixing parameters. And the time-frequency masking is used to recover the sources by evaluating the various ITDs and ILDs. Experimental results demonstrate the competitive performance of the proposed algorithm compared with the baseline algorithms.展开更多
In the paper the new subclasses■and■of the function class∑of bi-univalent functions involving the Hohlov operator are introduced and investigated.Then,the corresponding Fekete-Szeg functional inequalities as well a...In the paper the new subclasses■and■of the function class∑of bi-univalent functions involving the Hohlov operator are introduced and investigated.Then,the corresponding Fekete-Szeg functional inequalities as well as the bound estimates of the coefficients a2 and a3 are obtained.Furthermore,several consequences and connections to some of the earlier known results also are given.展开更多
In many deformation analyses,the partial derivatives at the interpolated scattered data points are required.In this paper,the Gaussian Radial Basis Functions(GRBF)is proposed for the interpolation and differentiation ...In many deformation analyses,the partial derivatives at the interpolated scattered data points are required.In this paper,the Gaussian Radial Basis Functions(GRBF)is proposed for the interpolation and differentiation of the scattered data in the vertical deformation analysis.For the optimal selection of the shape parameter,which is crucial in the GRBF interpolation,two methods are used:the Power Gaussian Radial Basis Functions(PGRBF)and Leave One Out Cross Validation(LOOCV)(LGRBF).We compared the PGRBF and LGRBF to the traditional interpolation methods such as the Finite Element Method(FEM),polynomials,Moving Least Squares(MLS),and the usual GRBF in both the simulated and actual Interferometric Synthetic Aperture Radar(InSAR)data.The estimated results showed that the surface interpolation accuracy was greatly improved by LGRBF and PGRBF methods in comparison withFEM,polynomial,and MLS methods.Finally,LGRBF and PGRBF interpolation methods are used to compute invariant vertical deformation parameters,i.e.,changes in Gaussian and mean Curvatures in the Groningen area in the North of Netherlands.展开更多
Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing unit.Renewable energy sources are playing a significant rol...Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing unit.Renewable energy sources are playing a significant role in the modern energy system with rapid development.In renewable sources like fuel combustion and solar energy,the generated voltages change due to their environmental changes.To develop energy resources,electric power generation involved huge awareness.The power and output voltages are plays important role in our work but it not considered in the existing system.For considering the power and voltage,Gaussian PI Controller-Maxpooling Deep Convolutional Neural Network Classifier(GPIC-MDCNNC)Model is introduced for the grid-connected renewable energy system.The input information is collected from two input sources.After that,input layer transfer information to hidden layer 1 fuzzy PI is employed for controlling voltage in GPIC-MDCNNC Model.Hidden layer 1 is transferred to hidden layer 2.Gaussian activation is employed for determining the output voltage with help of the controller.At last,the output layer offers the last value in GPIC-MDCNNC Model.The designed method was confirmed using one and multiple sources by stable and unpredictable input voltages.GPIC-MDCNNC Model increases the performance of grid-connected renewable energy systems by enhanced voltage value compared with state-of-the-art works.The control technique using GPIC-MDCNNC Model increases the dynamics of hybrid energy systems connected to the grid.展开更多
To address the early separation problem in the Menter Shear-Stress Transport(SST)turbulence model,a correction for the Turbulent Kinetic Energy(TKE)production term,P_(k),is introduced to account for the effect of the ...To address the early separation problem in the Menter Shear-Stress Transport(SST)turbulence model,a correction for the Turbulent Kinetic Energy(TKE)production term,P_(k),is introduced to account for the effect of the Adverse Pressure Gradient(APG).The correction is determined based on the distribution of Pkin the APG region before separation.When the friction coefficient C_(f) is decomposed,its direct dependence on Pkis clearly observed.However,with the introduction of Bradshaw’s assumption,Pkin the SST turbulence model is over-suppressed,resulting in a lower inner peak or no significant inner peak distribution at all.To address this problem,this paper proposes a Gaussian function,HGauss,which corrects the numerical values of P_(k) involved in the calculation of the Menter SST model by focusing on the inner peak region of P_(k).The modified SST model is then applied to four cases with APGs.The modification leads to an increase in the wall friction coefficient C_(f)in the APG region and causes a downstream shift in the separation location,improving the model’s consistency with high-accuracy data and experimental results.It is demonstrated that this correction can improve the early separation problem in the Menter SST turbulence model.展开更多
Corneal topography serves as an essential reference for diagnostic treatment in ophthalmology.Accurate corneal topography is crucial for clinical practice.In this study,the refractive power calculation was performed b...Corneal topography serves as an essential reference for diagnostic treatment in ophthalmology.Accurate corneal topography is crucial for clinical practice.In this study,the refractive power calculation was performed based on the initial corneal information collected using the Placido disc.A corneal point cloud model was established in polar coordinates,and an interpolation algorithm was proposed to fill missing points of the local bicubic B-spline by searching control points in the selfdefined interpolation matrix.The grid interpolation of the point cloud information and the smooth imaging of the final topographic map were achieved by Delaunay triangulation and Gaussian kernel function smoothing.Experiment results show that the proposed interpolation algorithm has higher accuracy than previous algorithms.The mean absolute error between the measured diopter of the original detection and the reconstructed is less than 0.300 D,indicating that this algorithm is feasible.展开更多
An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filt...An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filters have been analyzed. Using linear modulating filters, we can obtain an identification model that is parameterized directly in continuous-time model parameters. By applying the results from discrete-time model identification to the obtained identification model, a continuous-time estimation method is developed. Considering the accuracy of parameter estimates, an instrumental variable (Ⅳ) method is proposed, and the design of modulating integral filter is discussed. The relationship between the accuracy of identification and the parameter of modulating filter is investigated, and some points about designing Gaussian wavelet modulating function are outlined. Finally, a simulation study is also included to verify the theoretical results.展开更多
In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System(SINS/GNSS)integrated navigation system,due to the factors such as the high dynamics,the signal blocking by obstacles,the sig...In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System(SINS/GNSS)integrated navigation system,due to the factors such as the high dynamics,the signal blocking by obstacles,the signal intefereces,etc.,there always exist pulse interferences or measurement information interruptions in the satellite receiver,which make nonstationary measurement process.The traditional Kalman Filter(KF)can tackle the state estimation problem under Gaussian white noise,but its performance will be significantly reduced under nonGaussian noises.In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems,a Maximum Versoria Criterion Extended Kalman Filter(MVC-EKF)algorithm is proposed based on the MVC and the idea of M-estimation,which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost.Finally,the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.展开更多
Phenology is an important indicator of climate change.Studying spatiotemporal variations in remote sensing phenology of vegetation can provide a basis for further analysis of global climate change.Based on time series...Phenology is an important indicator of climate change.Studying spatiotemporal variations in remote sensing phenology of vegetation can provide a basis for further analysis of global climate change.Based on time series data of MODIS-NDVI from 2000 to 2017,we extracted and analyzed four remote sensing phenological parameters of vegetation,including the Start of Season(SOS),the End of Season(EOS),the Middle of Season(MOS)and the Length of Season(LOS),in tundra-taiga transitional zone in the East Siberia,using asymmetric Gaussian function and dynamic threshold methods.Meanwhile,we analyzed the responses of the four phenological parameters to the temperature change based on the temperature change data from Climate Research Unit(CRU).The results show that:in regions south of 64°N,with the rise of temperature in April and May,the SOS in the corresponding area was 5-15 days ahead of schedule;in the area between 64°N and 72°N,with the rise of temperature in May and June,the SOS in the corresponding area was 10-25 days ahead of schedule;in the northernmost of the study area on the coast of the Arctic Ocean,with the drop of temperature in May and June,the SOS in the corresponding area was 15-25 days behind schedule;in the northwest of the study area in August and the southwest in September,with the drop of temperature,the EOS in the corresponding areas was 15-30 days ahead of schedule;in regions south of 67°N,with the rise of temperature in September and October,the EOS in the corresponding area was 5-30 days behind schedule;the change of the EOS in autumn was more sensitive to the change of the SOS in spring,because the smaller temperature fluctuation can cause the larger change of the EOS;the growth season of vegetation in the study area was generally moving forward,and the LOS in the northwest was shortened,while the LOS in the middle and south of the study area was prolonged.展开更多
Monitoring soil moisture is important for agriculture and forestry and plays an essential role in land surface processes as well as providing feedback among the earth’s surface ecosystems.Large-scale regional soil mo...Monitoring soil moisture is important for agriculture and forestry and plays an essential role in land surface processes as well as providing feedback among the earth’s surface ecosystems.Large-scale regional soil moisture spatial data can be obtained with a reliable and operational approach using remote sensing.In this paper,we provide an operational framework for retrieving soil moisture using laboratory spectral data.The inverted Gaussian function was used to fit soil spectral data,and its feature parameters,including absorption depth(AD)and absorption area(AA),were selected as variables for a soil moisture estimate model.There was a significant correlative relationship between soil moisture and AD,as well as AA near 1400 and 1900 nm.A one-variable linear regression model was established to estimate soil moisture.The model was evaluated using the determination coefficients(R2),root mean square error and average precision.Four models were established and evaluated in this study.The determination coefficients of the four models ranged from 0.794 to 0.845.The average accuracy for soil moisture estimates ranged from 90 to 92%.The results prove that it is feasible to estimate soil moisture using remote sensing technology.展开更多
Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on th...Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on the flowering stage, using its apparent structure features and colors. Additional phenological stages have been largely overlooked. The objective of this study was to improve a shape-model method(SMM) for extracting winter canola phenological stages from time-series top-of-canopy reflectance images collected by an unmanned aerial vehicle(UAV). The transformation equation of the SMM was refined to account for the multi-peak features of the temporal dynamics of three vegetation indices(VIs)(NDVI, EVI, and CI). An experiment with various seeding scenarios was conducted, including four different seeding dates and three seeding densities. Three mathematical functions: asymmetric Gaussian function(AGF), Fourier function, and double logistic function, were employed to fit timeseries vegetation indices to extract information about phenological stages. The refined SMM effectively estimated the phenological stages of canola, with a minimum root mean square error(RMSE) of 3.7 days for all phenological stages. The AGF function provided the best fitting performance, as it captured multiple peaks in the growth dynamics characteristics for all seeding date scenarios using four scaling parameters. For the three selected VIs, CIred-edgeachieved the greatest accuracy in estimating the phenological stage dates. This study demonstrates the high potential of the refined SMM for estimating winter canola phenology.展开更多
Beamlet sources have strong local and directional character and can easily accomplish local illumination and migration. Besides, they provide better migration results than conventional migration methods. We introduce ...Beamlet sources have strong local and directional character and can easily accomplish local illumination and migration. Besides, they provide better migration results than conventional migration methods. We introduce the basic principles of beamlet prestack depth migration that includes a windowed Fourier transform and frame theory. We explain the Gabor-Daubechies （G-D） frame based on a Gaussian function. Beamlet decomposition provides information on the local space and direction of wavefield. We synthesize the beamlet source and beamlet records in the wavelet domain using both rectangle and Gaussian windows and then extrapolate the synthesized data with a Fourier finite-difference operator. We test the method using the standard Marmousi model. By comparing and analyzing the migration results of single directional beamlet and beamlets with different windows and directions, we demonstrate the validity of the prestack depth migration with Gaussian beamlets method.展开更多
To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming c...To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new classes.The network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known dataset.On the one hand,the network is required to have the ability to distinguish whether two samples are from the same class.On the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set testing.During the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known classes.The simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.展开更多
Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spat...Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppean important part of global grasslandsis the largest and relatively well preserved grassland in the world. In this studywe analyzed the spatial pattern of aboveground biomass（AGB）and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources（literatureglobal NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center（ORNL）some data provided by other researchers）. Our results demonstrated that：（1） as for the Eurasian steppe overallthe spatial variation in AGB exhibited significant horizontal and vertical zonality. In detailAGB showed an inverted parabola curve with the latitude and with the elevationwhile a parabola curve with the longitude. In additionthe spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregionwhile horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion.（2） Of the examined environmental variablesthe spatial variation of AGB was related to mean annual precipitation（MAP）mean annual temperature（MAT）mean annual solar radiation（MAR）soil Gravel contentsoil p H and soil organic content（SOC） at the depth of 0–30 cm. NeverthelessMAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions.（3） A Gaussian function was found between AGB and MAP in the Eurasian steppe overallwhich was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion（elevation 〈 3000 m）the Mongolian Plateau steppe subregion（elevation 〈 3000 m） and the surface（elevation ≥ 4800 m） of the Tibetan Plateau. Neverthelessthe spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins（elevation 〈 4800 m） of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grasslandthe Tibetan Plateau alpine grasslandetc.展开更多
In designing the human comfort index (CI) used in Guangzhou, a Gaussian curve was adopted as the fundamental profile to develop a traw hat?model of comfort index. The model projects low or high temperatures into low i...In designing the human comfort index (CI) used in Guangzhou, a Gaussian curve was adopted as the fundamental profile to develop a traw hat?model of comfort index. The model projects low or high temperatures into low index values and the moderate temperatures into high index values. Air temperature was chosen as a basic factor in the model. Other factors such as humidity, sunshine and wind speed were introduced by considering them as temperature departures to an equivalent apparent temperature (EAT). Since the index is a relative index, 25C was chosen as an ideal apparent temperature (the most comfortable state) and a maximum CI value of 100 was assigned at this temperature. While in other circumstances, the index would be lower than 100. By utilizing this model, the daily comfort index values had been calculated for Guangzhou city for 1998-1999, using mean temperature, mean humidity, mean wind speed and total hours of sunshine. Results show that the new model was reasonable and practicable. Not only could it reflect the monthly variation of human comfort in Guangzhou, but also was sensitive to short-term changes of weather conditions.展开更多
Significant changes to the world’s climate over the past few decades have had an impact on the development of plants.Vegetation in high latitude regions,where the ecosystems are fragile,is susceptible to climate chan...Significant changes to the world’s climate over the past few decades have had an impact on the development of plants.Vegetation in high latitude regions,where the ecosystems are fragile,is susceptible to climate change.It is possible to better understand vegetation’s phenological response to climate change by examining these areas.Traditional studies have mainly investigated how a single meteorological factor affects changes in vegetation phenology through linear correlation analysis,which is insufficient for quantitatively revealing the effects of various climate factor interactions on changes in vegetation phenology.We used the asymmetric Gaussian method to fit the normalized difference vegetation index(NDVI)curve and then used the dynamic threshold method to extract the phenological parameters,including the start of the season(SOS),end of the season(EOS),and length of the season(LOS),of the vegetation in this study area in the Tundra-Tagar transitional zone in eastern and western Siberia from 2000 to 2017.The monthly temperature and precipitation data used in this study were obtained from the climate research unit(CRU)meteorological dataset.The degrees to which the changes in temperature and precipitation in the various months and their interactions affected the changes in the three phenological parameters were determined using the GeoDetector,and the results were explicable.The findings demonstrate that the EOS was more susceptible to climate change than the SOS.The vegetation phenology shift was best explained by the climate in March,April,and September,and the combined effect of the temperature and precipitation had a greater impact on the change in the vegetation phenology compared with the effects of the individual climate conditions.The results quantitatively show the degree of interaction between the variations in temperature and precipitation and their effects on the changes in the different phenological parameters in the various months.Understanding how various climatic variations effect phenology changes in plants at different times may be more intuitive.This research provides as a foundation for research on how global climate change affects ecosystems and the global carbon cycle.展开更多
In this paper,we present new bounds for the perimeter of an ellipse in terms of harmonic,geometric,arithmetic and quadratic means;these new bounds represent improvements upon some previously known results.
文摘The relations between Gaussian function and Γ function is revealed first at one dimensional situation. Then, the Fourier transformation of n dimensional Gaussian function is deduced by a lemma. Following the train of thought in one dimensional situation, the relation between n dimensional Gaussian function and Γ function is given. By these, the possibility of arbitrary derivative of an n dimensional Gaussian function being a mother wavelet is indicated. The result will take some enlightening role in exploring the internal relations between Gaussian function and Γ function as well as in finding high dimensional mother wavelets.
基金supported by Shanghai 2021“Science and Technology Innovation Action Plan”:Social Development Science and Technology Research Project(Grant No.21DZ1202703).
文摘The numerical simulation of the fluid flow and the flexible rod(s)interaction is more complicated and has lower efficiency due to the high computational cost.In this paper,a semi-resolved model coupling the computational fluid dynamics and the flexible rod dynamics is proposed using a two-way domain expansion method.The gov-erning equations of the flexible rod dynamics are discretized and solved by the finite element method,and the fluid flow is simulated by the finite volume method.The interaction between fluids and solid rods is modeled by introducing body force terms into the momentum equations.Referred to the traditional semi-resolved numerical model,an anisotropic Gaussian kernel function method is proposed to specify the interactive forces between flu-ids and solid bodies for non-circle rod cross-sections.A benchmark of the flow passing around a single flexible plate with a rectangular cross-section is used to validate the algorithm.Focused on the engineering applications,a test case of a finite patch of cylinders is implemented to validate the accuracy and efficiency of the coupled model.
文摘The performance of two models,Jam and Baig,based on the modified version of Gaussian distribution function in estimating the daily total of global solar radiation and its distribution through the hours of the day from sunrise to sunset al any clear day is evaluated with our own measured data in the period from June 1992 to May 1993 in Qena Egypt The results show a high relative deviation of calculated values from measured ones,especially for Jain model,in the most hours of the day,except for those near to local noon.This misfit behavior is quite obvious in the early morning and late afternoon A new approach has been proposed in this paper to estimate the daily and hourly global solar radiation This model performs with very high accuracy on the recorded data in our region.The validity of this approach was verified with new measurements in some clear days in June and August 1994.The resultant very low relative deviation of the calculated values of global solar radiation from the measured ones confirms the high performance of the approach proposed in this work
基金supported by the National Natural Science Foundation of China(Grant Nos.61162014,61210306074)the Natural Science Foundation of Jiangxi Province of China(Grant No.20122BAB201025)the Foundation for Young Scientists of Jiangxi Province(Jinggang Star)(Grant No.20122BCB23002)
文摘Most existing algorithms for the underdetermined blind source separation(UBSS) problem are two-stage algorithm, i.e., mixing parameters estimation and sources estimation. In the mixing parameters estimation, the previously proposed traditional clustering algorithms are sensitive to the initializations of the mixing parameters. To reduce the sensitiveness to the initialization, we propose a new algorithm for the UBSS problem based on anechoic speech mixtures by employing the visual information, i.e., the interaural time difference(ITD) and the interaural level difference(ILD), as the initializations of the mixing parameters. In our algorithm, the video signals are utilized to estimate the distances between microphones and sources, and then the estimations of the ITD and ILD can be obtained. With the sparsity assumption in the time-frequency domain, the Gaussian potential function algorithm is utilized to estimate the mixing parameters by using the ITDs and ILDs as the initializations of the mixing parameters. And the time-frequency masking is used to recover the sources by evaluating the various ITDs and ILDs. Experimental results demonstrate the competitive performance of the proposed algorithm compared with the baseline algorithms.
基金Supported by Science and Technology Research Project of Colleges and Universities in Ningxia(Grant No.NGY2017011)Program for Young Talents of Science and Technology in Universities of Inner Mongolia Autonomous Region(Grant No.NJYT-18-44)+1 种基金the Natural Science Foundation of Inner Mongolia(Grant No.2018MS01026)the Natural Science Foundation of China(Grant Nos.11561055,11561001,11762016)
文摘In the paper the new subclasses■and■of the function class∑of bi-univalent functions involving the Hohlov operator are introduced and investigated.Then,the corresponding Fekete-Szeg functional inequalities as well as the bound estimates of the coefficients a2 and a3 are obtained.Furthermore,several consequences and connections to some of the earlier known results also are given.
文摘In many deformation analyses,the partial derivatives at the interpolated scattered data points are required.In this paper,the Gaussian Radial Basis Functions(GRBF)is proposed for the interpolation and differentiation of the scattered data in the vertical deformation analysis.For the optimal selection of the shape parameter,which is crucial in the GRBF interpolation,two methods are used:the Power Gaussian Radial Basis Functions(PGRBF)and Leave One Out Cross Validation(LOOCV)(LGRBF).We compared the PGRBF and LGRBF to the traditional interpolation methods such as the Finite Element Method(FEM),polynomials,Moving Least Squares(MLS),and the usual GRBF in both the simulated and actual Interferometric Synthetic Aperture Radar(InSAR)data.The estimated results showed that the surface interpolation accuracy was greatly improved by LGRBF and PGRBF methods in comparison withFEM,polynomial,and MLS methods.Finally,LGRBF and PGRBF interpolation methods are used to compute invariant vertical deformation parameters,i.e.,changes in Gaussian and mean Curvatures in the Groningen area in the North of Netherlands.
文摘Multi-port converters are considered as exceeding earlier period decade owing to function in a combination of different energy sources in a single processing unit.Renewable energy sources are playing a significant role in the modern energy system with rapid development.In renewable sources like fuel combustion and solar energy,the generated voltages change due to their environmental changes.To develop energy resources,electric power generation involved huge awareness.The power and output voltages are plays important role in our work but it not considered in the existing system.For considering the power and voltage,Gaussian PI Controller-Maxpooling Deep Convolutional Neural Network Classifier(GPIC-MDCNNC)Model is introduced for the grid-connected renewable energy system.The input information is collected from two input sources.After that,input layer transfer information to hidden layer 1 fuzzy PI is employed for controlling voltage in GPIC-MDCNNC Model.Hidden layer 1 is transferred to hidden layer 2.Gaussian activation is employed for determining the output voltage with help of the controller.At last,the output layer offers the last value in GPIC-MDCNNC Model.The designed method was confirmed using one and multiple sources by stable and unpredictable input voltages.GPIC-MDCNNC Model increases the performance of grid-connected renewable energy systems by enhanced voltage value compared with state-of-the-art works.The control technique using GPIC-MDCNNC Model increases the dynamics of hybrid energy systems connected to the grid.
基金supported by the National Natural Science Foundation of China(No.92252201)。
文摘To address the early separation problem in the Menter Shear-Stress Transport(SST)turbulence model,a correction for the Turbulent Kinetic Energy(TKE)production term,P_(k),is introduced to account for the effect of the Adverse Pressure Gradient(APG).The correction is determined based on the distribution of Pkin the APG region before separation.When the friction coefficient C_(f) is decomposed,its direct dependence on Pkis clearly observed.However,with the introduction of Bradshaw’s assumption,Pkin the SST turbulence model is over-suppressed,resulting in a lower inner peak or no significant inner peak distribution at all.To address this problem,this paper proposes a Gaussian function,HGauss,which corrects the numerical values of P_(k) involved in the calculation of the Menter SST model by focusing on the inner peak region of P_(k).The modified SST model is then applied to four cases with APGs.The modification leads to an increase in the wall friction coefficient C_(f)in the APG region and causes a downstream shift in the separation location,improving the model’s consistency with high-accuracy data and experimental results.It is demonstrated that this correction can improve the early separation problem in the Menter SST turbulence model.
基金Shanghai Science and Technology Program,China (No.20DZ2251400)。
文摘Corneal topography serves as an essential reference for diagnostic treatment in ophthalmology.Accurate corneal topography is crucial for clinical practice.In this study,the refractive power calculation was performed based on the initial corneal information collected using the Placido disc.A corneal point cloud model was established in polar coordinates,and an interpolation algorithm was proposed to fill missing points of the local bicubic B-spline by searching control points in the selfdefined interpolation matrix.The grid interpolation of the point cloud information and the smooth imaging of the final topographic map were achieved by Delaunay triangulation and Gaussian kernel function smoothing.Experiment results show that the proposed interpolation algorithm has higher accuracy than previous algorithms.The mean absolute error between the measured diopter of the original detection and the reconstructed is less than 0.300 D,indicating that this algorithm is feasible.
基金This project was supported by China Postdoctoral Science Foundation (2003034466)Scientific Research Fund of Hunan Provincial Education Department (02B032).
文摘An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filters have been analyzed. Using linear modulating filters, we can obtain an identification model that is parameterized directly in continuous-time model parameters. By applying the results from discrete-time model identification to the obtained identification model, a continuous-time estimation method is developed. Considering the accuracy of parameter estimates, an instrumental variable (Ⅳ) method is proposed, and the design of modulating integral filter is discussed. The relationship between the accuracy of identification and the parameter of modulating filter is investigated, and some points about designing Gaussian wavelet modulating function are outlined. Finally, a simulation study is also included to verify the theoretical results.
基金co-supported by the National Natural Science Foundation of China(No.62073264)the Key Research and Development Project of Shaanxi Province,China(No.2021ZDLGY01-01 and 2020ZDLGY06-02)+2 种基金National Natural Science Foundation of China(No.61803309)China Postdoctoral Science Foundation(No.2018M633574)the Aeronautical Science Foundation of China(No.2019ZA053008)。
文摘In the missile-borne Strapdown Inertial Navigation System/Global Navigation Satellite System(SINS/GNSS)integrated navigation system,due to the factors such as the high dynamics,the signal blocking by obstacles,the signal intefereces,etc.,there always exist pulse interferences or measurement information interruptions in the satellite receiver,which make nonstationary measurement process.The traditional Kalman Filter(KF)can tackle the state estimation problem under Gaussian white noise,but its performance will be significantly reduced under nonGaussian noises.In order to deal with the non-Gaussian conditions in the actual missile-borne SINS/GNSS integrated navigation systems,a Maximum Versoria Criterion Extended Kalman Filter(MVC-EKF)algorithm is proposed based on the MVC and the idea of M-estimation,which assigns a smaller weight to the anomalous measurements so as to suppress the influence of anomalous measurements on the state estimation while maintaining a relatively low calculation cost.Finally,the integrated navigation simulation experiments prove the effectiveness and robustness of the proposed algorithm.
基金Major Special Project-The China High-Resolution Earth Observation System,No.30-Y20A07-9003-17/18。
文摘Phenology is an important indicator of climate change.Studying spatiotemporal variations in remote sensing phenology of vegetation can provide a basis for further analysis of global climate change.Based on time series data of MODIS-NDVI from 2000 to 2017,we extracted and analyzed four remote sensing phenological parameters of vegetation,including the Start of Season(SOS),the End of Season(EOS),the Middle of Season(MOS)and the Length of Season(LOS),in tundra-taiga transitional zone in the East Siberia,using asymmetric Gaussian function and dynamic threshold methods.Meanwhile,we analyzed the responses of the four phenological parameters to the temperature change based on the temperature change data from Climate Research Unit(CRU).The results show that:in regions south of 64°N,with the rise of temperature in April and May,the SOS in the corresponding area was 5-15 days ahead of schedule;in the area between 64°N and 72°N,with the rise of temperature in May and June,the SOS in the corresponding area was 10-25 days ahead of schedule;in the northernmost of the study area on the coast of the Arctic Ocean,with the drop of temperature in May and June,the SOS in the corresponding area was 15-25 days behind schedule;in the northwest of the study area in August and the southwest in September,with the drop of temperature,the EOS in the corresponding areas was 15-30 days ahead of schedule;in regions south of 67°N,with the rise of temperature in September and October,the EOS in the corresponding area was 5-30 days behind schedule;the change of the EOS in autumn was more sensitive to the change of the SOS in spring,because the smaller temperature fluctuation can cause the larger change of the EOS;the growth season of vegetation in the study area was generally moving forward,and the LOS in the northwest was shortened,while the LOS in the middle and south of the study area was prolonged.
基金supported by the National Natural Science Foundation of China(No.31500519)the Fundamental Research Funds for the Central Universities(No.2572017BA06)the National Natural Science Foundation of China(No.31500518,31470640)
文摘Monitoring soil moisture is important for agriculture and forestry and plays an essential role in land surface processes as well as providing feedback among the earth’s surface ecosystems.Large-scale regional soil moisture spatial data can be obtained with a reliable and operational approach using remote sensing.In this paper,we provide an operational framework for retrieving soil moisture using laboratory spectral data.The inverted Gaussian function was used to fit soil spectral data,and its feature parameters,including absorption depth(AD)and absorption area(AA),were selected as variables for a soil moisture estimate model.There was a significant correlative relationship between soil moisture and AD,as well as AA near 1400 and 1900 nm.A one-variable linear regression model was established to estimate soil moisture.The model was evaluated using the determination coefficients(R2),root mean square error and average precision.Four models were established and evaluated in this study.The determination coefficients of the four models ranged from 0.794 to 0.845.The average accuracy for soil moisture estimates ranged from 90 to 92%.The results prove that it is feasible to estimate soil moisture using remote sensing technology.
基金supported by the National Natural Science Foundation of China (51909228)the Postdoctoral Science Foundation of China (2020M671623)the ‘‘Blue Project” of Yangzhou University。
文摘Accurate information about phenological stages is essential for canola field management practices such as irrigation, fertilization, and harvesting. Previous studies in canola phenology monitoring focused mainly on the flowering stage, using its apparent structure features and colors. Additional phenological stages have been largely overlooked. The objective of this study was to improve a shape-model method(SMM) for extracting winter canola phenological stages from time-series top-of-canopy reflectance images collected by an unmanned aerial vehicle(UAV). The transformation equation of the SMM was refined to account for the multi-peak features of the temporal dynamics of three vegetation indices(VIs)(NDVI, EVI, and CI). An experiment with various seeding scenarios was conducted, including four different seeding dates and three seeding densities. Three mathematical functions: asymmetric Gaussian function(AGF), Fourier function, and double logistic function, were employed to fit timeseries vegetation indices to extract information about phenological stages. The refined SMM effectively estimated the phenological stages of canola, with a minimum root mean square error(RMSE) of 3.7 days for all phenological stages. The AGF function provided the best fitting performance, as it captured multiple peaks in the growth dynamics characteristics for all seeding date scenarios using four scaling parameters. For the three selected VIs, CIred-edgeachieved the greatest accuracy in estimating the phenological stage dates. This study demonstrates the high potential of the refined SMM for estimating winter canola phenology.
基金This project is sponsored by the National Natural Science Foundation （40474041）, CNPC Young Innovation Fund （04E7040）, the Post-doctoral Research Station of Zhongyuan 0ilfield, Jiangsu 0ilfield, and CNPC Geophysical Laboratories at the China University of Petroleum （East China）.
文摘Beamlet sources have strong local and directional character and can easily accomplish local illumination and migration. Besides, they provide better migration results than conventional migration methods. We introduce the basic principles of beamlet prestack depth migration that includes a windowed Fourier transform and frame theory. We explain the Gabor-Daubechies （G-D） frame based on a Gaussian function. Beamlet decomposition provides information on the local space and direction of wavefield. We synthesize the beamlet source and beamlet records in the wavelet domain using both rectangle and Gaussian windows and then extrapolate the synthesized data with a Fourier finite-difference operator. We test the method using the standard Marmousi model. By comparing and analyzing the migration results of single directional beamlet and beamlets with different windows and directions, we demonstrate the validity of the prestack depth migration with Gaussian beamlets method.
基金supported by the National Natural Science Foundation of China(U19B2016)Zhejiang Provincial Key Lab of Data Storage and Transmission Technology,Hangzhou Dianzi University。
文摘To improve the recognition ability of communication jamming signals,Siamese Neural Network-based Open World Recognition(SNNOWR)is proposed.The algorithm can recognize known jamming classes,detect new(unknown)jamming classes,and unsupervised cluseter new classes.The network of SNN-OWR is trained supervised with paired input data consisting of two samples from a known dataset.On the one hand,the network is required to have the ability to distinguish whether two samples are from the same class.On the other hand,the latent distribution of known class is forced to approach their own unique Gaussian distribution,which is prepared for the subsequent open set testing.During the test,the unknown class detection process based on Gaussian probability density function threshold is designed,and an unsupervised clustering algorithm of the unknown jamming is realized by using the prior knowledge of known classes.The simulation results show that when the jamming-to-noise ratio is more than 0d B,the accuracy of SNN-OWR algorithm for known jamming classes recognition,unknown jamming detection and unsupervised clustering of unknown jamming is about 95%.This indicates that the SNN-OWR algorithm can make the effect of the recognition of unknown jamming be almost the same as that of known jamming.
基金The Chinese Academy of Sciences Strategic Priority Research Program,No.XDA05050602The Key Program of National Natural Science Foundation of China,No.31290221
文摘Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppean important part of global grasslandsis the largest and relatively well preserved grassland in the world. In this studywe analyzed the spatial pattern of aboveground biomass（AGB）and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources（literatureglobal NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center（ORNL）some data provided by other researchers）. Our results demonstrated that：（1） as for the Eurasian steppe overallthe spatial variation in AGB exhibited significant horizontal and vertical zonality. In detailAGB showed an inverted parabola curve with the latitude and with the elevationwhile a parabola curve with the longitude. In additionthe spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregionwhile horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion.（2） Of the examined environmental variablesthe spatial variation of AGB was related to mean annual precipitation（MAP）mean annual temperature（MAT）mean annual solar radiation（MAR）soil Gravel contentsoil p H and soil organic content（SOC） at the depth of 0–30 cm. NeverthelessMAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions.（3） A Gaussian function was found between AGB and MAP in the Eurasian steppe overallwhich was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion（elevation 〈 3000 m）the Mongolian Plateau steppe subregion（elevation 〈 3000 m） and the surface（elevation ≥ 4800 m） of the Tibetan Plateau. Neverthelessthe spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins（elevation 〈 4800 m） of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grasslandthe Tibetan Plateau alpine grasslandetc.
文摘In designing the human comfort index (CI) used in Guangzhou, a Gaussian curve was adopted as the fundamental profile to develop a traw hat?model of comfort index. The model projects low or high temperatures into low index values and the moderate temperatures into high index values. Air temperature was chosen as a basic factor in the model. Other factors such as humidity, sunshine and wind speed were introduced by considering them as temperature departures to an equivalent apparent temperature (EAT). Since the index is a relative index, 25C was chosen as an ideal apparent temperature (the most comfortable state) and a maximum CI value of 100 was assigned at this temperature. While in other circumstances, the index would be lower than 100. By utilizing this model, the daily comfort index values had been calculated for Guangzhou city for 1998-1999, using mean temperature, mean humidity, mean wind speed and total hours of sunshine. Results show that the new model was reasonable and practicable. Not only could it reflect the monthly variation of human comfort in Guangzhou, but also was sensitive to short-term changes of weather conditions.
基金International Cooperation and Exchange of the National Natural Science Foundation of China,No.42061134019Major Special Project-The China High-Resolution Earth Observation System,No.30-Y30F06-9003-20/22。
文摘Significant changes to the world’s climate over the past few decades have had an impact on the development of plants.Vegetation in high latitude regions,where the ecosystems are fragile,is susceptible to climate change.It is possible to better understand vegetation’s phenological response to climate change by examining these areas.Traditional studies have mainly investigated how a single meteorological factor affects changes in vegetation phenology through linear correlation analysis,which is insufficient for quantitatively revealing the effects of various climate factor interactions on changes in vegetation phenology.We used the asymmetric Gaussian method to fit the normalized difference vegetation index(NDVI)curve and then used the dynamic threshold method to extract the phenological parameters,including the start of the season(SOS),end of the season(EOS),and length of the season(LOS),of the vegetation in this study area in the Tundra-Tagar transitional zone in eastern and western Siberia from 2000 to 2017.The monthly temperature and precipitation data used in this study were obtained from the climate research unit(CRU)meteorological dataset.The degrees to which the changes in temperature and precipitation in the various months and their interactions affected the changes in the three phenological parameters were determined using the GeoDetector,and the results were explicable.The findings demonstrate that the EOS was more susceptible to climate change than the SOS.The vegetation phenology shift was best explained by the climate in March,April,and September,and the combined effect of the temperature and precipitation had a greater impact on the change in the vegetation phenology compared with the effects of the individual climate conditions.The results quantitatively show the degree of interaction between the variations in temperature and precipitation and their effects on the changes in the different phenological parameters in the various months.Understanding how various climatic variations effect phenology changes in plants at different times may be more intuitive.This research provides as a foundation for research on how global climate change affects ecosystems and the global carbon cycle.
基金supported by the Natural Science Foundation of China(11971142)the Natural Science Foundation of Zhejiang Province(LY19A010012)。
文摘In this paper,we present new bounds for the perimeter of an ellipse in terms of harmonic,geometric,arithmetic and quadratic means;these new bounds represent improvements upon some previously known results.
