Because of the fractional order derivatives, the identification of the fractional order system（FOS） is more complex than that of an integral order system（IOS）. In order to avoid high time consumption in the system...Because of the fractional order derivatives, the identification of the fractional order system（FOS） is more complex than that of an integral order system（IOS）. In order to avoid high time consumption in the system identification, the leastsquares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method.展开更多
A fast physics analysis framework has been developed based on SNi PER to process the increasingly large data sample collected by BESⅢ.In this framework,a reconstructed event data model with Smart Ref is designed to i...A fast physics analysis framework has been developed based on SNi PER to process the increasingly large data sample collected by BESⅢ.In this framework,a reconstructed event data model with Smart Ref is designed to improve the speed of Input/Output operations,and necessary physics analysis tools are migrated from BOSS to SNi PER.A real physics analysis e~＋e^-→ π~＋π^-J/ψ is used to test the new framework,and achieves a factor of10.3 improvement in Input/Output speed compared to BOSS.Further tests show that the improvement is mainly attributed to the new reconstructed event data model and the lazy-loading functionality provided by Smart Ref.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61271395)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20161513)
文摘Because of the fractional order derivatives, the identification of the fractional order system（FOS） is more complex than that of an integral order system（IOS）. In order to avoid high time consumption in the system identification, the leastsquares method is used to find other parameters by fixing the fractional derivative order. Hereafter, the optimal parameters of a system will be found by varying the derivative order in an interval. In addition, the operational matrix of the fractional order integration combined with the multi-resolution nature of a wavelet is used to accelerate the FOS identification, which is achieved by discarding wavelet coefficients of high-frequency components of input and output signals. In the end, the identifications of some known fractional order systems and an elastic torsion system are used to verify the proposed method.
基金Supported by Joint Large-Scale Scientific Facility Funds of the NSFC and CAS(U1532258)Program for New Century Excellent Talents in University(NCET-13-0342)+1 种基金Shandong Natural Science Funds for Distinguished Young Scholar(JQ201402)National Key Basic Research Program of China under Contract(2015CB856700)
文摘A fast physics analysis framework has been developed based on SNi PER to process the increasingly large data sample collected by BESⅢ.In this framework,a reconstructed event data model with Smart Ref is designed to improve the speed of Input/Output operations,and necessary physics analysis tools are migrated from BOSS to SNi PER.A real physics analysis e~＋e^-→ π~＋π^-J/ψ is used to test the new framework,and achieves a factor of10.3 improvement in Input/Output speed compared to BOSS.Further tests show that the improvement is mainly attributed to the new reconstructed event data model and the lazy-loading functionality provided by Smart Ref.
