对非线性时滞离散动态系统的最优控制,提出了一种信息融合估计(information fusion estimation,IFE)方法,把非线性控制问题的所有信息转化为关于控制量的 ..
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Their precision and computational burdens are compared. They can be applied into optimal information fusion estimation for the states or signals.
文中比较了三种融合估计的精度和计算负担，可应用于信息融合状态或信号最优估计。
The filtering methods based on information fusion estimation in linear or nonlinear systems was presented for the filtering problem in discrete dynamic stochastic system.
针对离散随机动态系统的滤波问题，提出了基于信息融合估计的线性和非线性滤波方法。
Based on Multi_sensor Multi_model information, we present a new algorithm based on total information fusion estimation on target state. We prove the validity of this algorithm by computer.
基于多传感器多模型信息，给出了目标状态基于全局信息融合估计的一种新算法，并通过计算机仿真验证了这种算法的有效性。
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