Stochastic system state estimation subject to the unknown interference input widely exists in many fields,such as the control,communication,signal processing,and fault diagnosis.However,the research results are mostly...Stochastic system state estimation subject to the unknown interference input widely exists in many fields,such as the control,communication,signal processing,and fault diagnosis.However,the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input,and the state model and the measurement model are both with the same unknown interference input.State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs(dual-UI)with different physical meanings and mathematical definitions is concerned here.Firstly,the decoupling condition with the Unknown Interference input in the State model(S-UI)is shown,which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs(M-UI)appearing in the state model and the measurement model.Then,through defining the Differential term of the adjacent M-UI(M-UID),the equivalent system with only M-UID in the state model is obtained.Finally,considering the design freedom of the equivalent system,the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate,respectively.Two simulation cases verify the effectiveness and superiority compared with the traditional methods.展开更多
In this article, a new approach for modeling multiinput multi-output （MIMO） systems with unknown nonlinear interference is introduced. The semiparametric theory based MIMO model is established, and Kernel estimation...In this article, a new approach for modeling multiinput multi-output （MIMO） systems with unknown nonlinear interference is introduced. The semiparametric theory based MIMO model is established, and Kernel estimation is applied to combat the nonlinear interference. Furthermore, we derive MIMO capacity for these systems and explore the asymptotic properties of the new channel matrix via theoretical analysis. The simulation results show that the semiparametric theory based modeling and kernel estimation are valid to combat this kind of interference.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61603040 and 61433003)Yunnan Applied Basic Research Project of China(No.201701CF00037)+1 种基金Guangdong Province Science and Technology Innovation Strategy Special Fund Project,China(No.skjtdzxrwqd2018001)Yunnan Provincial Science and Technology Department Key Research Program(Engineering),China(No.2018BA070)。
文摘Stochastic system state estimation subject to the unknown interference input widely exists in many fields,such as the control,communication,signal processing,and fault diagnosis.However,the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input,and the state model and the measurement model are both with the same unknown interference input.State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs(dual-UI)with different physical meanings and mathematical definitions is concerned here.Firstly,the decoupling condition with the Unknown Interference input in the State model(S-UI)is shown,which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs(M-UI)appearing in the state model and the measurement model.Then,through defining the Differential term of the adjacent M-UI(M-UID),the equivalent system with only M-UID in the state model is obtained.Finally,considering the design freedom of the equivalent system,the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate,respectively.Two simulation cases verify the effectiveness and superiority compared with the traditional methods.
基金the National Natural Science Foundation of China（60496312）；the Hi-Tech Research and Development Program of China （2006AA01Z260）；the Program for New Century Excellent Talents in University（NCET-05-116）.
文摘In this article, a new approach for modeling multiinput multi-output （MIMO） systems with unknown nonlinear interference is introduced. The semiparametric theory based MIMO model is established, and Kernel estimation is applied to combat the nonlinear interference. Furthermore, we derive MIMO capacity for these systems and explore the asymptotic properties of the new channel matrix via theoretical analysis. The simulation results show that the semiparametric theory based modeling and kernel estimation are valid to combat this kind of interference.
