针对卫星网络中卫星载重有限,不允许大规模部署物理硬件,导致其网络功能欠缺且网络管理和配置不灵活的问题,文中提出了基于软件定义网络(Software Defined Networking,SDN)/网络功能虚拟化(Network Function Virtualization,NFV)协同部...针对卫星网络中卫星载重有限,不允许大规模部署物理硬件,导致其网络功能欠缺且网络管理和配置不灵活的问题,文中提出了基于软件定义网络(Software Defined Networking,SDN)/网络功能虚拟化(Network Function Virtualization,NFV)协同部署的卫星网络新架构。它通过SDN数控分离思想对网络进行动态管控,利用NFV技术在SDN的数字平面虚拟出网络功能,使网络功能能够从硬件设备中解耦出来,从而提高网络的灵活性。为了解决此框架中虚拟网络功能(Virtual Network Function,VNF)映射到底层物理网络上的时延过大且无法满足高动态卫星网络实时性的问题,进一步提出了Viterbi和图形模式匹配(Graph Pattern Matching,GPM)相结合的动态映射方法(Viterbi and GPM Dynamic Placement Approach,VG-DPA)。该算法将映射过程建模为隐马尔可夫服务链,采用Viterbi算法预计算满足软硬件限制的映射路径,然后根据预计算结果通过GPM来制定VNF编排策略。该算法解决了卫星网络中将所需的VNF映射到底层物理网络中时延过大的问题。实验结果表明,VG-DPA与传统的RAND和OMD算法相比能在很大程度上降低时延,减少资源消耗。展开更多
In this paper, an emotional mathematical model and affective state probability description space of a humanoid robot are set up on the basis of psycho-dynamics＇ psychological energy and affective energy conservation ...In this paper, an emotional mathematical model and affective state probability description space of a humanoid robot are set up on the basis of psycho-dynamics＇ psychological energy and affective energy conservation law. The emotional state transferring process and hidden Markov chain algorithm of stimulating transition process are then studied. The simulation results show that the mathematical model is applicable to the authentic affective state change rule of human beings. Finally, the gait generation experiment results of control signal and electric current tracking wave-form are presented to demonstrate the validity of the proposed mathematical model.展开更多
In this paper, we study the optimal investment and proportional reinsurance strategy for an insurer in a hidden Markov regime-switching environment. A risk-based approach is considered, where the insurer aims at selec...In this paper, we study the optimal investment and proportional reinsurance strategy for an insurer in a hidden Markov regime-switching environment. A risk-based approach is considered, where the insurer aims at selecting an optimal strategy with a view to minimizing the risk described by a convex risk measure of its terminal wealth. We solve the problem in two steps. First, we employ the filtering theory to turn the optimization problem with partial observations into one with complete observations. Second, by using BSDEs with jumps, we solve the problem with complete observations.展开更多
The stage of a tumor is sometimes hard to predict, especially early in its development. The size and complexity of its observations are the major problems that lead to false diagnoses. Even experienced doctors can mak...The stage of a tumor is sometimes hard to predict, especially early in its development. The size and complexity of its observations are the major problems that lead to false diagnoses. Even experienced doctors can make a mistake in causing terrible consequences for the patient. We propose a mathematical tool for the diagnosis of breast cancer. The aim is to help specialists in making a decision on the likelihood of a patient’s condition knowing the series of observations available. This may increase the patient’s chances of recovery. With a multivariate observational hidden Markov model, we describe the evolution of the disease by taking the geometric properties of the tumor as observable variables. The latent variable corresponds to the type of tumor: malignant or benign. The analysis of the covariance matrix makes it possible to delineate the zones of occurrence for each group belonging to a type of tumors. It is therefore possible to summarize the properties that characterize each of the tumor categories using the parameters of the model. These parameters highlight the differences between the types of tumors.展开更多
This paper investigates the optimal reinsurance and investment in a hidden Markov financial market consisting of non-risky （bond） and risky （stock） asset. We assume that only the price of the risky asset can be ob...This paper investigates the optimal reinsurance and investment in a hidden Markov financial market consisting of non-risky （bond） and risky （stock） asset. We assume that only the price of the risky asset can be observed from the financial market. Suppose that the insurance company can adopt proportional reinsurance and investment in the hidden Markov financial market to reduce risk or increase profit. Our objective is to maximize the expected exponential utility of the terminal wealth of the surplus of the insurance company. By using the filtering theory, we establish the separation principle and reduce the problem to the complete information case. With the help of Girsanov change of measure and the dynamic programming approach, we characterize the value function as the unique solution of a linear parabolic partial differential equation and obtain the Feynman-Kac representation of the value function.展开更多
Aspects of human behavior in cyber security allow more natural security to the user. This research focuses the appearance of anticipating cyber threats and their abstraction hierarchy levels on the mental picture leve...Aspects of human behavior in cyber security allow more natural security to the user. This research focuses the appearance of anticipating cyber threats and their abstraction hierarchy levels on the mental picture levels of human. The study concerns the modeling of the behaviors of mental states of an individual under cyber attacks. The mental state of agents being not observable, we propose a non-stationary hidden Markov chain approach to model the agent mental behaviors. A renewal process based on a nonparametric estimation is also considered to investigate the spending time in a given mental state. In these approaches, the effects of the complexity of the cyber attacks are taken into account in the models.展开更多
文摘针对卫星网络中卫星载重有限,不允许大规模部署物理硬件,导致其网络功能欠缺且网络管理和配置不灵活的问题,文中提出了基于软件定义网络(Software Defined Networking,SDN)/网络功能虚拟化(Network Function Virtualization,NFV)协同部署的卫星网络新架构。它通过SDN数控分离思想对网络进行动态管控,利用NFV技术在SDN的数字平面虚拟出网络功能,使网络功能能够从硬件设备中解耦出来,从而提高网络的灵活性。为了解决此框架中虚拟网络功能(Virtual Network Function,VNF)映射到底层物理网络上的时延过大且无法满足高动态卫星网络实时性的问题,进一步提出了Viterbi和图形模式匹配(Graph Pattern Matching,GPM)相结合的动态映射方法(Viterbi and GPM Dynamic Placement Approach,VG-DPA)。该算法将映射过程建模为隐马尔可夫服务链,采用Viterbi算法预计算满足软硬件限制的映射路径,然后根据预计算结果通过GPM来制定VNF编排策略。该算法解决了卫星网络中将所需的VNF映射到底层物理网络中时延过大的问题。实验结果表明,VG-DPA与传统的RAND和OMD算法相比能在很大程度上降低时延,减少资源消耗。
基金supported by National High Technology Research and Development Program of China (863 Program)(No.2007AA04Z218)
文摘In this paper, an emotional mathematical model and affective state probability description space of a humanoid robot are set up on the basis of psycho-dynamics＇ psychological energy and affective energy conservation law. The emotional state transferring process and hidden Markov chain algorithm of stimulating transition process are then studied. The simulation results show that the mathematical model is applicable to the authentic affective state change rule of human beings. Finally, the gait generation experiment results of control signal and electric current tracking wave-form are presented to demonstrate the validity of the proposed mathematical model.
基金Supported by the National Natural Science Foundation of China(No.11371284)the Fundamental Research Funds for the Central Universities(WUT:2015IVA066)
文摘In this paper, we study the optimal investment and proportional reinsurance strategy for an insurer in a hidden Markov regime-switching environment. A risk-based approach is considered, where the insurer aims at selecting an optimal strategy with a view to minimizing the risk described by a convex risk measure of its terminal wealth. We solve the problem in two steps. First, we employ the filtering theory to turn the optimization problem with partial observations into one with complete observations. Second, by using BSDEs with jumps, we solve the problem with complete observations.
文摘The stage of a tumor is sometimes hard to predict, especially early in its development. The size and complexity of its observations are the major problems that lead to false diagnoses. Even experienced doctors can make a mistake in causing terrible consequences for the patient. We propose a mathematical tool for the diagnosis of breast cancer. The aim is to help specialists in making a decision on the likelihood of a patient’s condition knowing the series of observations available. This may increase the patient’s chances of recovery. With a multivariate observational hidden Markov model, we describe the evolution of the disease by taking the geometric properties of the tumor as observable variables. The latent variable corresponds to the type of tumor: malignant or benign. The analysis of the covariance matrix makes it possible to delineate the zones of occurrence for each group belonging to a type of tumors. It is therefore possible to summarize the properties that characterize each of the tumor categories using the parameters of the model. These parameters highlight the differences between the types of tumors.
基金Supported by National Natural Science Foundation of China(NSFC grant No.11371020,71302156)
文摘This paper investigates the optimal reinsurance and investment in a hidden Markov financial market consisting of non-risky （bond） and risky （stock） asset. We assume that only the price of the risky asset can be observed from the financial market. Suppose that the insurance company can adopt proportional reinsurance and investment in the hidden Markov financial market to reduce risk or increase profit. Our objective is to maximize the expected exponential utility of the terminal wealth of the surplus of the insurance company. By using the filtering theory, we establish the separation principle and reduce the problem to the complete information case. With the help of Girsanov change of measure and the dynamic programming approach, we characterize the value function as the unique solution of a linear parabolic partial differential equation and obtain the Feynman-Kac representation of the value function.
文摘Aspects of human behavior in cyber security allow more natural security to the user. This research focuses the appearance of anticipating cyber threats and their abstraction hierarchy levels on the mental picture levels of human. The study concerns the modeling of the behaviors of mental states of an individual under cyber attacks. The mental state of agents being not observable, we propose a non-stationary hidden Markov chain approach to model the agent mental behaviors. A renewal process based on a nonparametric estimation is also considered to investigate the spending time in a given mental state. In these approaches, the effects of the complexity of the cyber attacks are taken into account in the models.
