Independent component analysis (ICA) is the primary statistical method for solving the problems of blind source separation. The fast ICA is a famous and excellent algorithm and its contrast function is optimized by ...Independent component analysis (ICA) is the primary statistical method for solving the problems of blind source separation. The fast ICA is a famous and excellent algorithm and its contrast function is optimized by the quadratic convergence of Newton iteration method. In order to improve the convergence speed and the separation precision of the fast ICA, an improved fast ICA algorithm is presented. The algorithm introduces an efficient Newton's iterative method with fifth-order convergence for optimizing the contrast function and gives the detail derivation process and the corresponding condition. The experimental results demonstrate that the convergence speed and the separation precision of the improved algorithm are better than that of the fast ICA.展开更多
A small target detection approach based on independent component analysis for hyperspectral data is put forward. In this algorithm, firstly the fast independent component analysis(FICA) is used to collect target infor...A small target detection approach based on independent component analysis for hyperspectral data is put forward. In this algorithm, firstly the fast independent component analysis(FICA) is used to collect target information hided in high-dimensional data and projects them into low-dimensional space.Secondly, the feature images are selected with kurtosis .At last, small targets are extracted with histogram image segmentation which has been labeled by skewness.展开更多
The purpose of the present study is to develop a methodology to evaluate fuel discharge through the CRGT (control-rod guide tube) during CDAs (core-disruptive accidents) of SFRs (sodium-cooled fast reactors), si...The purpose of the present study is to develop a methodology to evaluate fuel discharge through the CRGT (control-rod guide tube) during CDAs (core-disruptive accidents) of SFRs (sodium-cooled fast reactors), since fuel discharge will decrease the core reactivity and CRGTs have a potential to provide an effective discharge path. Fuel discharge contains multi-component fluid dynamics with phase changes, and, in the present study, the SFR safety analysis code SIMMER (Sn, implicit, multifield, multicomponent, Eulerian recriticality) was utilized as a technical basis. First, dominant phenomena affecting fuel discharge through the CRGT are identified based on parametric calculations by the SIMMER code. Next, validations on the code models closely relating to these phenomena were carried out based on experimental data. It was shown that the SIMMER code with some model modifications could reproduce the experimental results appropriately. Through the present study, the evaluation methodology for the molten-fuel discharge through the CRGT was successfully developed.展开更多
Unmanned Aerial Vehicles(UAVs)are widely used and meet many demands in military and civilian fields.With the continuous enrichment and extensive expansion of application scenarios,the safety of UAVs is constantly bein...Unmanned Aerial Vehicles(UAVs)are widely used and meet many demands in military and civilian fields.With the continuous enrichment and extensive expansion of application scenarios,the safety of UAVs is constantly being challenged.To address this challenge,we propose algorithms to detect anomalous data collected from drones to improve drone safety.We deployed a one-class kernel extreme learning machine(OCKELM)to detect anomalies in drone data.By default,OCKELM uses the radial basis(RBF)kernel function as the kernel function of themodel.To improve the performance ofOCKELM,we choose a TriangularGlobalAlignmentKernel(TGAK)instead of anRBF Kernel and introduce the Fast Independent Component Analysis(FastICA)algorithm to reconstruct UAV data.Based on the above improvements,we create a novel anomaly detection strategy FastICA-TGAK-OCELM.The method is finally validated on the UCI dataset and detected on the Aeronautical Laboratory Failures and Anomalies(ALFA)dataset.The experimental results show that compared with other methods,the accuracy of this method is improved by more than 30%,and point anomalies are effectively detected.展开更多
The properties of the same pigments in murals are affected by different concentrations and particle diameters,which cause the shape of the spectral reflectance data curve to vary,thus influencing the outcome of matchi...The properties of the same pigments in murals are affected by different concentrations and particle diameters,which cause the shape of the spectral reflectance data curve to vary,thus influencing the outcome of matching calculations.This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences.Fast principal component analysis(FPCA)was used to calculate the eigenvalue variance of pigment spectral reflectance,then applied to the original reflectance values for parameter characterization.We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral curve.Secondly,the relative distance between the eigenvalues in the eigen variance space is combined with the JS(Jensen-Shannon)divergence to express the difference between the two spectral distributions.The JS information divergence calculates the relative distance between the eigenvalues.Experimental results showthat our classification method can be used to identify the spectral curves of the same pigment under different states.The value of the root means square error(RMSE)decreased by 12.0817,while the mean values of the mean absolute percentage error(MAPE)and R2 increased by 0.0965 and 0.2849,respectively.Compared with the traditional spectral matching algorithm,the recognition error was effectively reduced.展开更多
Neurons at rest can exhibit diverse firing activities patterns in response to various external deterministic and random stimuli, especially additional currents. In this paper, neuronal firing patterns from bursting to...Neurons at rest can exhibit diverse firing activities patterns in response to various external deterministic and random stimuli, especially additional currents. In this paper, neuronal firing patterns from bursting to spiking, induced by additional direct and stochastic currents, are explored in rest states corresponding to two values of the parameter VK in the Chay neuron system. Three cases are considered by numerical simulation and fast/slow dynamic analysis, in which only the direct current or the stochastic current exists, or the direct and stochastic currents coexist. Meanwhile, several important bursting patterns in neuronal experiments, such as the period-1 "circle/homoclinic" bursting and the integer multiple "fold/homoclinic" bursting with onc spike per burst, as well as the transition from integer multiple bursting to period-1 "circle/homoclinic" bursting and that from stochastic "Hopf/homoclinic" bursting to "Hopf/homoclinic" bursting, are investigated in detail.展开更多
Numerical simulation modeling is a hotspot in the geological engineering computing field. Tak- ing a fast Langrangian analysis of continua in 3 dimensions (FLAC3D) numerical modeling on com- puting the geo-deformati...Numerical simulation modeling is a hotspot in the geological engineering computing field. Tak- ing a fast Langrangian analysis of continua in 3 dimensions (FLAC3D) numerical modeling on com- puting the geo-deformation information caused by the mining subsidence in a coalmine for example, a new GIS-Excel modeling method is proposed to build geologic strata within the simulation range combined with the coal-seam dip angle of the underground mining working-planes. First of all, the coal-seam model of the numerical computing is built by using the geographic information system (GIS) according to the stripe-through principle and the calculating formula on the size of the model blocks in the paper defined, then the FLAC3D numerical computing model of all geologic strata with- in the simulation range is also built based on the calculating formula of thickness of each stratum and the Excel fast computing advantages. The GIS-Excel method is good at the higher modeling accuracy, seldom making mistakes and consuming less time. The reliability and validity of the method is veri- fied well by its practical applications in the coalmine area.展开更多
In order to realize the high speed data acquisition and fast Fourier analysis, the paper put forward a kind of high speed data acquisition and analysis system based on FPGA, the system uses Cyclone series FPGA with hi...In order to realize the high speed data acquisition and fast Fourier analysis, the paper put forward a kind of high speed data acquisition and analysis system based on FPGA, the system uses Cyclone series FPGA with high-speed A/D converter, and use the fast Fourier custom analysis nucleation of Altera company, using the standard TCP/IP protocol communication with PC, match up the master machine based on Matlab GUI analysis software. We experiment high speed data acquisition and fast Fourier analysis for a plurality of groups of high frequency analog signals, at the same time the results display on the computer. The experimental results validate the fast Fourier analysis theory, and has realized the low cost, high performance data acquisition and analysis of the complete system design.展开更多
This paper presents an efficient supply current wave shaping technique for bridgeless interleaved Single Ended Primary Inductor Converter(SEPIC).The SEPIC converter converts an Alternating Current(AC)to Direct Current...This paper presents an efficient supply current wave shaping technique for bridgeless interleaved Single Ended Primary Inductor Converter(SEPIC).The SEPIC converter converts an Alternating Current(AC)to Direct Current(DC)with the boost converter.Power Factor Correction(PFC)is progressively significant to achieve high energy efficiency.The overall system efficiency can be increased as the bridgeless topology has less conduction losses from rectifying bridges.Also,the bridgeless and interleaved techniques are incorporated in this study to achieve better performance.The performance of the system is analyzed on both current control and sensor-less techniques.Different controllers such as Proportional Integral(PI)control,peak current control,Non-Linear Carrier(NLC)control,and sensor-less current control are integrated.All the above controllers are implemented using MATrix LABoratory(MATLAB)/SIMULINK.The performance parameter,namely Power Factor(PF),Total Harmonic Distortion(THD),is computed for both open loop and closed loop condition.The sensor-less current control method is implemented using the DsPIC30F2010 controller.The circuit performance is also verified from the simulation and hardware results.The proposed controller has inbuilt Analog-to-Digital Converter(ADC),Digital-to-Analog Converter(DAC),Pulse Width Modulation(PWM)generator,and provides fast responses.展开更多
The generic phantom bursting model proposed by Bertram et al.can evoke complex bursting oscillations in collaboration with two generic slow variables with different time scales.Two models with the phantom bursting mec...The generic phantom bursting model proposed by Bertram et al.can evoke complex bursting oscillations in collaboration with two generic slow variables with different time scales.Two models with the phantom bursting mechanism are suggested,when these two generic slow variables are provided with some specific biological significances by combining slowly varying intracellular Ca2+concentration of the Chay-Keizer electrical bursting model with two different glycolytic oscillations,respectively.Also,complex dynamic behaviors of different compound bursting occurring in these two models are comprehensively surveyed by two fast/slow analyses for a moderately and a slower slow variable,respectively.展开更多
文摘Independent component analysis (ICA) is the primary statistical method for solving the problems of blind source separation. The fast ICA is a famous and excellent algorithm and its contrast function is optimized by the quadratic convergence of Newton iteration method. In order to improve the convergence speed and the separation precision of the fast ICA, an improved fast ICA algorithm is presented. The algorithm introduces an efficient Newton's iterative method with fifth-order convergence for optimizing the contrast function and gives the detail derivation process and the corresponding condition. The experimental results demonstrate that the convergence speed and the separation precision of the improved algorithm are better than that of the fast ICA.
基金Funded by the National 863 Program of China (No.2002AA783050)
文摘A small target detection approach based on independent component analysis for hyperspectral data is put forward. In this algorithm, firstly the fast independent component analysis(FICA) is used to collect target information hided in high-dimensional data and projects them into low-dimensional space.Secondly, the feature images are selected with kurtosis .At last, small targets are extracted with histogram image segmentation which has been labeled by skewness.
文摘The purpose of the present study is to develop a methodology to evaluate fuel discharge through the CRGT (control-rod guide tube) during CDAs (core-disruptive accidents) of SFRs (sodium-cooled fast reactors), since fuel discharge will decrease the core reactivity and CRGTs have a potential to provide an effective discharge path. Fuel discharge contains multi-component fluid dynamics with phase changes, and, in the present study, the SFR safety analysis code SIMMER (Sn, implicit, multifield, multicomponent, Eulerian recriticality) was utilized as a technical basis. First, dominant phenomena affecting fuel discharge through the CRGT are identified based on parametric calculations by the SIMMER code. Next, validations on the code models closely relating to these phenomena were carried out based on experimental data. It was shown that the SIMMER code with some model modifications could reproduce the experimental results appropriately. Through the present study, the evaluation methodology for the molten-fuel discharge through the CRGT was successfully developed.
基金supported by the Natural Science Foundation of The Jiangsu Higher Education Institutions of China(Grant No.19JKB520031).
文摘Unmanned Aerial Vehicles(UAVs)are widely used and meet many demands in military and civilian fields.With the continuous enrichment and extensive expansion of application scenarios,the safety of UAVs is constantly being challenged.To address this challenge,we propose algorithms to detect anomalous data collected from drones to improve drone safety.We deployed a one-class kernel extreme learning machine(OCKELM)to detect anomalies in drone data.By default,OCKELM uses the radial basis(RBF)kernel function as the kernel function of themodel.To improve the performance ofOCKELM,we choose a TriangularGlobalAlignmentKernel(TGAK)instead of anRBF Kernel and introduce the Fast Independent Component Analysis(FastICA)algorithm to reconstruct UAV data.Based on the above improvements,we create a novel anomaly detection strategy FastICA-TGAK-OCELM.The method is finally validated on the UCI dataset and detected on the Aeronautical Laboratory Failures and Anomalies(ALFA)dataset.The experimental results show that compared with other methods,the accuracy of this method is improved by more than 30%,and point anomalies are effectively detected.
基金This work was supported in part by the National Science Foundation of China:Shaanxi Natural Science Basic Research Project(2021JM-377)Science and Technology Cooperation Project of Shaanxi Provincial Department of Science and Technology(2020KW-012)University Talent Service Enterprise Project of Xi’an Science and Technology Bureau(GXYD10.1)。
文摘The properties of the same pigments in murals are affected by different concentrations and particle diameters,which cause the shape of the spectral reflectance data curve to vary,thus influencing the outcome of matching calculations.This paper proposes a spectral matching classification method of multi-state similar pigments based on feature differences.Fast principal component analysis(FPCA)was used to calculate the eigenvalue variance of pigment spectral reflectance,then applied to the original reflectance values for parameter characterization.We first projected the original spectral reflectance from the spectral space to the characteristic variance space to identify the spectral curve.Secondly,the relative distance between the eigenvalues in the eigen variance space is combined with the JS(Jensen-Shannon)divergence to express the difference between the two spectral distributions.The JS information divergence calculates the relative distance between the eigenvalues.Experimental results showthat our classification method can be used to identify the spectral curves of the same pigment under different states.The value of the root means square error(RMSE)decreased by 12.0817,while the mean values of the mean absolute percentage error(MAPE)and R2 increased by 0.0965 and 0.2849,respectively.Compared with the traditional spectral matching algorithm,the recognition error was effectively reduced.
基金Project supported by the National Natural Science Foundation of China (Grant Nos 10432010 and 10526002).Acknowledgement The bifurcation diagrams in this paper are obtained by means of the package C0NTENT.
文摘Neurons at rest can exhibit diverse firing activities patterns in response to various external deterministic and random stimuli, especially additional currents. In this paper, neuronal firing patterns from bursting to spiking, induced by additional direct and stochastic currents, are explored in rest states corresponding to two values of the parameter VK in the Chay neuron system. Three cases are considered by numerical simulation and fast/slow dynamic analysis, in which only the direct current or the stochastic current exists, or the direct and stochastic currents coexist. Meanwhile, several important bursting patterns in neuronal experiments, such as the period-1 "circle/homoclinic" bursting and the integer multiple "fold/homoclinic" bursting with onc spike per burst, as well as the transition from integer multiple bursting to period-1 "circle/homoclinic" bursting and that from stochastic "Hopf/homoclinic" bursting to "Hopf/homoclinic" bursting, are investigated in detail.
基金Supported by the National Natural Science Foundation of China(No.41271436)
文摘Numerical simulation modeling is a hotspot in the geological engineering computing field. Tak- ing a fast Langrangian analysis of continua in 3 dimensions (FLAC3D) numerical modeling on com- puting the geo-deformation information caused by the mining subsidence in a coalmine for example, a new GIS-Excel modeling method is proposed to build geologic strata within the simulation range combined with the coal-seam dip angle of the underground mining working-planes. First of all, the coal-seam model of the numerical computing is built by using the geographic information system (GIS) according to the stripe-through principle and the calculating formula on the size of the model blocks in the paper defined, then the FLAC3D numerical computing model of all geologic strata with- in the simulation range is also built based on the calculating formula of thickness of each stratum and the Excel fast computing advantages. The GIS-Excel method is good at the higher modeling accuracy, seldom making mistakes and consuming less time. The reliability and validity of the method is veri- fied well by its practical applications in the coalmine area.
文摘In order to realize the high speed data acquisition and fast Fourier analysis, the paper put forward a kind of high speed data acquisition and analysis system based on FPGA, the system uses Cyclone series FPGA with high-speed A/D converter, and use the fast Fourier custom analysis nucleation of Altera company, using the standard TCP/IP protocol communication with PC, match up the master machine based on Matlab GUI analysis software. We experiment high speed data acquisition and fast Fourier analysis for a plurality of groups of high frequency analog signals, at the same time the results display on the computer. The experimental results validate the fast Fourier analysis theory, and has realized the low cost, high performance data acquisition and analysis of the complete system design.
文摘This paper presents an efficient supply current wave shaping technique for bridgeless interleaved Single Ended Primary Inductor Converter(SEPIC).The SEPIC converter converts an Alternating Current(AC)to Direct Current(DC)with the boost converter.Power Factor Correction(PFC)is progressively significant to achieve high energy efficiency.The overall system efficiency can be increased as the bridgeless topology has less conduction losses from rectifying bridges.Also,the bridgeless and interleaved techniques are incorporated in this study to achieve better performance.The performance of the system is analyzed on both current control and sensor-less techniques.Different controllers such as Proportional Integral(PI)control,peak current control,Non-Linear Carrier(NLC)control,and sensor-less current control are integrated.All the above controllers are implemented using MATrix LABoratory(MATLAB)/SIMULINK.The performance parameter,namely Power Factor(PF),Total Harmonic Distortion(THD),is computed for both open loop and closed loop condition.The sensor-less current control method is implemented using the DsPIC30F2010 controller.The circuit performance is also verified from the simulation and hardware results.The proposed controller has inbuilt Analog-to-Digital Converter(ADC),Digital-to-Analog Converter(DAC),Pulse Width Modulation(PWM)generator,and provides fast responses.
基金supported by the National Natural Science Foundation of China(Grant Nos.1137201711072013 and 11202083)
文摘The generic phantom bursting model proposed by Bertram et al.can evoke complex bursting oscillations in collaboration with two generic slow variables with different time scales.Two models with the phantom bursting mechanism are suggested,when these two generic slow variables are provided with some specific biological significances by combining slowly varying intracellular Ca2+concentration of the Chay-Keizer electrical bursting model with two different glycolytic oscillations,respectively.Also,complex dynamic behaviors of different compound bursting occurring in these two models are comprehensively surveyed by two fast/slow analyses for a moderately and a slower slow variable,respectively.