On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random in...On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering （EKF） and the unscented Kalman filtering （UKF）, which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network （RBFNN） prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent.展开更多
为了控制Arduino的随机睡眠与唤醒,不采用"预定睡眠-随机唤醒"的常规设计模式,而是通过一个外部中断随机使Arduino进入睡眠,并且通过同一个外部中断随机唤醒Arduino。首先使用开源Enerlib和LowPower库对Arduino Pro Mini进行...为了控制Arduino的随机睡眠与唤醒,不采用"预定睡眠-随机唤醒"的常规设计模式,而是通过一个外部中断随机使Arduino进入睡眠,并且通过同一个外部中断随机唤醒Arduino。首先使用开源Enerlib和LowPower库对Arduino Pro Mini进行实验,然后应用于实际的工程设计中,取得了很好的效果。该方法可以作为成熟的方案推广到工程设计的实际应用当中。展开更多
基金Project supported by the State Key Program of the National Natural Science of China (Grant No. 60835004)the Natural Science Foundation of Jiangsu Province of China (Grant No. BK2009727)+1 种基金the Natural Science Foundation of Higher Education Institutions of Jiangsu Province of China (Grant No. 10KJB510004)the National Natural Science Foundation of China (Grant No. 61075028)
文摘On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering （EKF） and the unscented Kalman filtering （UKF）, which were shortened as GEKF and CUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network （RBFNN） prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent.
文摘为了控制Arduino的随机睡眠与唤醒,不采用"预定睡眠-随机唤醒"的常规设计模式,而是通过一个外部中断随机使Arduino进入睡眠,并且通过同一个外部中断随机唤醒Arduino。首先使用开源Enerlib和LowPower库对Arduino Pro Mini进行实验,然后应用于实际的工程设计中,取得了很好的效果。该方法可以作为成熟的方案推广到工程设计的实际应用当中。
