The basal theory of Gauss-MRF is expounded and 2-5 order Gauss MRF models are established. Parameters of the 2-5 order Gauss-MRF models for 300 wood samples＇ surface texture are also estimated by using LMS. The data ...The basal theory of Gauss-MRF is expounded and 2-5 order Gauss MRF models are established. Parameters of the 2-5 order Gauss-MRF models for 300 wood samples＇ surface texture are also estimated by using LMS. The data analysis shows that： 1） different rexture parameters have a clear scattered distribution, 2） the main direction of texture is the direction represented by the maximum parameter of Gauss-MRF parameters, and 3） for those samples having the same main direction, the finer the texture is, the greater the corresponding parameter is, and the smaller the other parameters are; and the higher the order of Gauss-MRF is, the more clearly the texture is described. On the condition of the second order Gauss MRF model, parameter B1, B2 of tangential texture are smaller than that of radial texture, while B3 and B4 of tangential texture are greater than that of radial texture. According to the value of separated criterion, the parameter of the fifth order Gauss-MRF is used as feature vector for Hamming neural network classification. As a result, the ratio of correctness reaches 88%.展开更多
Background The lead-scintillating fiber electromagnetic calorimeter(ECAL)of the Alpha Magnetic Spectrometer measures the energy of positrons/electrons and separates them from hadrons.The electromagnetic shower shapes ...Background The lead-scintillating fiber electromagnetic calorimeter(ECAL)of the Alpha Magnetic Spectrometer measures the energy of positrons/electrons and separates them from hadrons.The electromagnetic shower shapes from Monte Carlo(MC)simulation and data show disagreement.Purpose Tuning the MC to make the shower shapes from MC and data agree with each other.Methods The tuning is based on a 3D electromagnetic shower model.Results After tuning,the electromagnetic shower shapes are well described by MC up to TeV.As a result,the output of ECAL electron/proton separation estimator,ECAL BDT,shows thatMCand data are in good agreement.The proton rejection power of the ECAL BDT trained with MC electron samples is improved by a factor of 5 at∼800 GeV compared to the one trained with data.展开更多
基金This paper is supported by the Municipal Natural Science Foundation of Harbin （2004AFX X J 0 20） and Provincial Natural Science Foundation of Heilongjiang （C2004-03）.
文摘The basal theory of Gauss-MRF is expounded and 2-5 order Gauss MRF models are established. Parameters of the 2-5 order Gauss-MRF models for 300 wood samples＇ surface texture are also estimated by using LMS. The data analysis shows that： 1） different rexture parameters have a clear scattered distribution, 2） the main direction of texture is the direction represented by the maximum parameter of Gauss-MRF parameters, and 3） for those samples having the same main direction, the finer the texture is, the greater the corresponding parameter is, and the smaller the other parameters are; and the higher the order of Gauss-MRF is, the more clearly the texture is described. On the condition of the second order Gauss MRF model, parameter B1, B2 of tangential texture are smaller than that of radial texture, while B3 and B4 of tangential texture are greater than that of radial texture. According to the value of separated criterion, the parameter of the fifth order Gauss-MRF is used as feature vector for Hamming neural network classification. As a result, the ratio of correctness reaches 88%.
文摘Background The lead-scintillating fiber electromagnetic calorimeter(ECAL)of the Alpha Magnetic Spectrometer measures the energy of positrons/electrons and separates them from hadrons.The electromagnetic shower shapes from Monte Carlo(MC)simulation and data show disagreement.Purpose Tuning the MC to make the shower shapes from MC and data agree with each other.Methods The tuning is based on a 3D electromagnetic shower model.Results After tuning,the electromagnetic shower shapes are well described by MC up to TeV.As a result,the output of ECAL electron/proton separation estimator,ECAL BDT,shows thatMCand data are in good agreement.The proton rejection power of the ECAL BDT trained with MC electron samples is improved by a factor of 5 at∼800 GeV compared to the one trained with data.
