The optimality of two-stage state estimation with ARMA model random bias is studiedin this paper. Firstly, the optimal augmented state Kalman filter is given; Secondly, the two-stageKalman estimator is designed. Final...The optimality of two-stage state estimation with ARMA model random bias is studiedin this paper. Firstly, the optimal augmented state Kalman filter is given; Secondly, the two-stageKalman estimator is designed. Finally, under an algebraic constraint condition, the equivalencebetween the two-stage Kalman estimator and the optimal augmented state Kalman filter is proved.Thereby, the algebraic constraint conditions of optimal two-stage state estimation in the presence ofARMA model random bias are given.展开更多
We propose a biased random number generation protocol whose randomness is based on the violation of the Clauser Home inequality. Non-maximally entangled state is used to maximize the Bell violation. Due to the rotatio...We propose a biased random number generation protocol whose randomness is based on the violation of the Clauser Home inequality. Non-maximally entangled state is used to maximize the Bell violation. Due to the rotational asymmetry of the quantum state, the ratio of Os to ls varies with the measurement bases. The experimental partners can then use their measurement outcomes to generate the biased random bit string. The bias of their bit string can be adjusted by altering their choices of measurement bases. When this protocol is implemented in a device-independent way, we show that the bias of the bit string can still be ensured under the collective attack.展开更多
The random walk (RW) is a very important model in science and engineering researches. It has been studied over hundreds years. However, there are still some overlooked problems on the RW. Here, we study the mean absol...The random walk (RW) is a very important model in science and engineering researches. It has been studied over hundreds years. However, there are still some overlooked problems on the RW. Here, we study the mean absolute distance of an N-step biased random walk (BRW) in a d-dimensional hyper-cubic lattice. In this short paper, we report the exact results for d = 1 and approximation formulae for d ≥ 2.展开更多
现有大多数用于识别候选疾病基因的随机游走方法通常优先访问高度连接的基因,而可能与已知疾病有关的不知名或连接性差的基因易被忽略或难以识别.此外,这些方法仅访问单个基因网络或各种基因数据的聚合网络,导致偏差和不完整性.因此,设...现有大多数用于识别候选疾病基因的随机游走方法通常优先访问高度连接的基因,而可能与已知疾病有关的不知名或连接性差的基因易被忽略或难以识别.此外,这些方法仅访问单个基因网络或各种基因数据的聚合网络,导致偏差和不完整性.因此,设计一种能控制随机游走运动方向和整合多种数据源的候选疾病基因识别方法将是一个迫切需要解决的问题.为此,首先构建多层网络和多层异构基因网络.然后,提出一种游走于多层网络和多层异构网络的拓扑偏置重启随机游走(Biased random walk with restart,BRWR)算法来识别疾病基因.实验结果表明,游走于不同类型网络上的识别候选疾病基因的BRWR算法优于现有的算法.最后,应用于多层异构网络上的BRWR算法能预测未诊断的新生儿类早衰综合征中涉及的疾病基因.展开更多
文摘The optimality of two-stage state estimation with ARMA model random bias is studiedin this paper. Firstly, the optimal augmented state Kalman filter is given; Secondly, the two-stageKalman estimator is designed. Finally, under an algebraic constraint condition, the equivalencebetween the two-stage Kalman estimator and the optimal augmented state Kalman filter is proved.Thereby, the algebraic constraint conditions of optimal two-stage state estimation in the presence ofARMA model random bias are given.
基金Supported by the National Natural Science Foundation of China under Grant Nos 61378011,U1204616 and 11447143the Program for Science and Technology Innovation Talents in Universities of Henan Province under Grant No 2012HASTIT028the Program for Science and Technology Innovation Research Team in University of Henan Province under Grant No 13IRTSTHN020
文摘We propose a biased random number generation protocol whose randomness is based on the violation of the Clauser Home inequality. Non-maximally entangled state is used to maximize the Bell violation. Due to the rotational asymmetry of the quantum state, the ratio of Os to ls varies with the measurement bases. The experimental partners can then use their measurement outcomes to generate the biased random bit string. The bias of their bit string can be adjusted by altering their choices of measurement bases. When this protocol is implemented in a device-independent way, we show that the bias of the bit string can still be ensured under the collective attack.
文摘The random walk (RW) is a very important model in science and engineering researches. It has been studied over hundreds years. However, there are still some overlooked problems on the RW. Here, we study the mean absolute distance of an N-step biased random walk (BRW) in a d-dimensional hyper-cubic lattice. In this short paper, we report the exact results for d = 1 and approximation formulae for d ≥ 2.
文摘现有大多数用于识别候选疾病基因的随机游走方法通常优先访问高度连接的基因,而可能与已知疾病有关的不知名或连接性差的基因易被忽略或难以识别.此外,这些方法仅访问单个基因网络或各种基因数据的聚合网络,导致偏差和不完整性.因此,设计一种能控制随机游走运动方向和整合多种数据源的候选疾病基因识别方法将是一个迫切需要解决的问题.为此,首先构建多层网络和多层异构基因网络.然后,提出一种游走于多层网络和多层异构网络的拓扑偏置重启随机游走(Biased random walk with restart,BRWR)算法来识别疾病基因.实验结果表明,游走于不同类型网络上的识别候选疾病基因的BRWR算法优于现有的算法.最后,应用于多层异构网络上的BRWR算法能预测未诊断的新生儿类早衰综合征中涉及的疾病基因.
