A scattering correction method for a panel detector based cone beam computed tomography system is presented. First,the x-ray spectrum of the system is acquired by using the Monte Carlo simulation method.Secondly,scatt...A scattering correction method for a panel detector based cone beam computed tomography system is presented. First,the x-ray spectrum of the system is acquired by using the Monte Carlo simulation method.Secondly,scattered photon distribution is calculated and stored as correction matrixes by using the Monte Carlo simulation method according to scanned objects and computed tomography system specialties.Thirdly,scattered photons are removed from projection data by correction matrixes.A comparison of reconstruction image between before and after scattering correction demonstrates that the scattering correction method is effective for the panel detector based cone beam computed tomography system.展开更多
In this paper,a novel opportunistic scheduling(OS)scheme with antenna selection(AS)for the energy harvesting(EH)cooperative communication system where the relay can harvest energy from the source transmission is propo...In this paper,a novel opportunistic scheduling(OS)scheme with antenna selection(AS)for the energy harvesting(EH)cooperative communication system where the relay can harvest energy from the source transmission is proposed.In this considered scheme,we take into both traditional mathematical analysis and reinforcement learning(RL)scenarios with the power splitting(PS)factor constraint.For the case of traditional mathematical analysis of a fixed-PS factor,we derive an exact closed-form expressions for the ergodic capacity and outage probability in general signal-to-noise ratio(SNR)regime.Then,we combine the optimal PS factor with performance metrics to achieve the optimal transmission performance.Subsequently,based on the optimized PS factor,a RL technique called as Q-learning(QL)algorithm is proposed to derive the optimal antenna selection strategy.To highlight the performance advantage of the proposed QL with training the received SNR at the destination,we also examine the scenario of QL scheme with training channel between the relay and the destination.The results illustrate that,the optimized scheme is always superior to the fixed-PS factor scheme.In addition,a better system parameter setting with QL significantly outperforms the traditional mathematical analysis scheme.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.60672104 and 10527003)the National Basic Research Program of China(Grant No.2006CB705705)the Joint Research Foundation of Beijing Education Committee, China(Grant No.JD100010607)
文摘A scattering correction method for a panel detector based cone beam computed tomography system is presented. First,the x-ray spectrum of the system is acquired by using the Monte Carlo simulation method.Secondly,scattered photon distribution is calculated and stored as correction matrixes by using the Monte Carlo simulation method according to scanned objects and computed tomography system specialties.Thirdly,scattered photons are removed from projection data by correction matrixes.A comparison of reconstruction image between before and after scattering correction demonstrates that the scattering correction method is effective for the panel detector based cone beam computed tomography system.
基金supported in part by the National Natural Science Foundation of China under Grant 61720106003,Grant 61401165,Grant 61379006,Grant 61671144,and Grant 61701538in part by the Natural Science Foundation of Fujian Province under Grants 2015J01262+3 种基金in part by Promotion Program for Young and Middle-aged Teacher in Science and Technology Research of Huaqiao University under Grant ZQN-PY407in part by Science and Technology Innovation Teams of Henan Province for Colleges and Universities(17IRTSTHN014)in part by the Scientific and Technological Key Project of Henan Province under Grant 172102210080 and Grant 182102210449in part by the Collaborative Innovation Center for Aviation Economy Development of Henan Province。
文摘In this paper,a novel opportunistic scheduling(OS)scheme with antenna selection(AS)for the energy harvesting(EH)cooperative communication system where the relay can harvest energy from the source transmission is proposed.In this considered scheme,we take into both traditional mathematical analysis and reinforcement learning(RL)scenarios with the power splitting(PS)factor constraint.For the case of traditional mathematical analysis of a fixed-PS factor,we derive an exact closed-form expressions for the ergodic capacity and outage probability in general signal-to-noise ratio(SNR)regime.Then,we combine the optimal PS factor with performance metrics to achieve the optimal transmission performance.Subsequently,based on the optimized PS factor,a RL technique called as Q-learning(QL)algorithm is proposed to derive the optimal antenna selection strategy.To highlight the performance advantage of the proposed QL with training the received SNR at the destination,we also examine the scenario of QL scheme with training channel between the relay and the destination.The results illustrate that,the optimized scheme is always superior to the fixed-PS factor scheme.In addition,a better system parameter setting with QL significantly outperforms the traditional mathematical analysis scheme.
