Background modeling and subtraction is a fundamental problem in video analysis. Many algorithms have been developed to date, but there are still some challenges in complex environments, especially dynamic scenes in wh...Background modeling and subtraction is a fundamental problem in video analysis. Many algorithms have been developed to date, but there are still some challenges in complex environments, especially dynamic scenes in which backgrounds are themselves moving, such as rippling water and swaying trees. In this paper, a novel background modeling method is proposed for dynamic scenes by combining both tensor representation and swarm intelligence. We maintain several video patches, which are naturally represented as higher order tensors,to represent the patterns of background, and utilize tensor low-rank approximation to capture the dynamic nature. Furthermore, we introduce an ant colony algorithm to improve the performance. Experimental results show that the proposed method is robust and adaptive in dynamic environments, and moving objects can be perfectly separated from the complex dynamic background.展开更多
In this paper, combining the transfer matrix method and the finite element method, the modified finite element transfer matrix method is presented for high efficient dynamic modeling of laminated plates. Then, by cons...In this paper, combining the transfer matrix method and the finite element method, the modified finite element transfer matrix method is presented for high efficient dynamic modeling of laminated plates. Then, by constructing the modal filter and the disturbance force observer, and using the feedback and feedforward approaches, the H ∞ independent modal space control strategy is designed for active vibration control of laminate plates subjected to arbitrary, immeasurable disturbance forces. Compared with ordinary dynamic modeling and control methods of laminated plate structures, the proposed method has the low memory requirement, high computational efficiency and robust control performance. Formulations as well as some numerical examples are given to validate the method and the control performance.展开更多
A Lagrangian modeling approach is applied to the numerical simulation of the temporal dynamics of a stage-structured population. The growth dynamics is determined only by the main biological processes： development of...A Lagrangian modeling approach is applied to the numerical simulation of the temporal dynamics of a stage-structured population. The growth dynamics is determined only by the main biological processes： development of an individual, mortality, reproduction. Different approaches in modeling the development process of an individual are implemented： stochastic advection-diffusion models （backward-forward dispersion models）, and stochastic development models where regression effects, defined as negative development on the status of an individual, are forbidden （forward dispersion models）. Some properties of the residence times of an individual in a stage are investigated： in particular, their role in the calibration of the development models and in the estimation of some parameters introduced in the model equation. As a study case a multi-stage pelagic copepod population is considered. Trying to separate the effects of the main biological processes on the temporal dynamics, numerical simulations have been carried out in some idealized situations： first only the development of the individuals, neglecting mortality and reproduction, is considered; then the mortality process is introduced, and finally both the mortality and reproduction processes. The results of the numerical simulations, are compared and discussed.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos. 11301137 and 11371036)the National Science Foundation of Hebei Province of China (Grant No. A2014205100
文摘Background modeling and subtraction is a fundamental problem in video analysis. Many algorithms have been developed to date, but there are still some challenges in complex environments, especially dynamic scenes in which backgrounds are themselves moving, such as rippling water and swaying trees. In this paper, a novel background modeling method is proposed for dynamic scenes by combining both tensor representation and swarm intelligence. We maintain several video patches, which are naturally represented as higher order tensors,to represent the patterns of background, and utilize tensor low-rank approximation to capture the dynamic nature. Furthermore, we introduce an ant colony algorithm to improve the performance. Experimental results show that the proposed method is robust and adaptive in dynamic environments, and moving objects can be perfectly separated from the complex dynamic background.
基金supported by the National Natural Science Foundation of China (Grant No. 10902051)the Natural Science Foundation of Jiangsu Province (Grant No. BK2008046)
文摘In this paper, combining the transfer matrix method and the finite element method, the modified finite element transfer matrix method is presented for high efficient dynamic modeling of laminated plates. Then, by constructing the modal filter and the disturbance force observer, and using the feedback and feedforward approaches, the H ∞ independent modal space control strategy is designed for active vibration control of laminate plates subjected to arbitrary, immeasurable disturbance forces. Compared with ordinary dynamic modeling and control methods of laminated plate structures, the proposed method has the low memory requirement, high computational efficiency and robust control performance. Formulations as well as some numerical examples are given to validate the method and the control performance.
文摘A Lagrangian modeling approach is applied to the numerical simulation of the temporal dynamics of a stage-structured population. The growth dynamics is determined only by the main biological processes： development of an individual, mortality, reproduction. Different approaches in modeling the development process of an individual are implemented： stochastic advection-diffusion models （backward-forward dispersion models）, and stochastic development models where regression effects, defined as negative development on the status of an individual, are forbidden （forward dispersion models）. Some properties of the residence times of an individual in a stage are investigated： in particular, their role in the calibration of the development models and in the estimation of some parameters introduced in the model equation. As a study case a multi-stage pelagic copepod population is considered. Trying to separate the effects of the main biological processes on the temporal dynamics, numerical simulations have been carried out in some idealized situations： first only the development of the individuals, neglecting mortality and reproduction, is considered; then the mortality process is introduced, and finally both the mortality and reproduction processes. The results of the numerical simulations, are compared and discussed.
