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model matching
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  model matching
We also propose the Haar wavelets method for 3D model matching.
      
A Distance Measure and a Feature Likelihood Map Concept for Scale-Invariant Model Matching
      
The key to making the proposed approach work is the use of appearance-based model matching and refinement which updates the estimated correspondences on each iteration of the algorithm.
      
This paper examines the connections between feedback stabilization and H∞ control, model matching problems and multivariable Nevanlinna-Pick interpolation problems for multidimensional or n-D linear systems.
      
In this paper, a new approach to the linear exact model matching problem for a class of nonlinear systems, using static state feedback, is presented.
      
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Most ATR methods deal with the single target. Actually, there are some targets arranged by some rules in spatial domain, which can be called "targets′ arrays". To recognize them, the spatial information among targets is used to make up the uncertainty of targets′ own features. A novel recognition approach of blob targets′ array at low resolution context (remote sensing images, infrared images, multi-spectrum images etc.) is presented. The method firstly utilizes the ARG model to customize the targets′ arrays...

Most ATR methods deal with the single target. Actually, there are some targets arranged by some rules in spatial domain, which can be called "targets′ arrays". To recognize them, the spatial information among targets is used to make up the uncertainty of targets′ own features. A novel recognition approach of blob targets′ array at low resolution context (remote sensing images, infrared images, multi-spectrum images etc.) is presented. The method firstly utilizes the ARG model to customize the targets′ arrays and combine the spatial relationships of array nodes and the targets′ other simple attributes. By estimating the probability density distribution of the spatial relationships among targets and their own features, the arrays can be recognized. The method is different from the classic ATR method which is based on ARG model matching. Instead, the method extracts the probability features of spatial information from ARG model directly to recognize. The experiments show that the method is effective.

以往目标识别技术多针对独立目标,但事实上目标有时会以成群的方式出现,目标之间呈现出明显的有规则的阵列分布关系,即目标阵列群。针对该类目标群的识别问题,可以通过提取目标群中子目标之间的空间分布关系的规律与特征,来弥补子目标的其他特征的不确定性。提出一种可有效识别低分辨率环境下(遥感、红外、多光谱等图像中)具有规则阵列分布特征的斑点目标集合的方法。该方法使用ARG模型描述目标阵列群,将目标相互之间的空间分布关系(距离关系)与目标自身的简单属性相结合,通过寻找空间分布关系特征与自身属性的统计规律,即估计特征的联合概率密度分布,利用其分布特点识别目标阵列群。

>=A TDF robust control method is proposed in designing an automatic pilot apparatus of BTT-missile. Based on the framework of the standard H∞ optimization theory, the conventional mixed sensitivity and model matching method is combined, and the parameters uncertainty and disturbances are considered in the process of missile flying. The simulation results are indicated that this methods have good robustness and stability in this paper.

在标准H∞框架上,提出了应用于BTT导弹的自动驾驶仪设计的两自由度的鲁棒控制方法,将混合灵敏度与模型匹配方法相结合,并考虑导弹飞行过程中的参数不确定和各种扰动,仿真结果表明本方法具有优越的鲁棒性和稳定性。

 
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