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unknown input
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  unknown input
Given an unknown input image, the recognition system projects the image to eigenspace.
      
The unique feature of the method is that it extends cycle-level architectural simulation techniques to enable symbolic execution with unknown input data values; it uses alternative instruction semantics to handle unknown operands.
      
(2004) International Journal of Control 77(9), 861-876], we develop a complete theory of dead-beat (possibly unknown input) observer-based fault detectors and isolators (FDIs).
      
(1986) IEEE Transactions on Automatic Control, AC-31, 676-680] and on some recent results about dead-beat unknown input observers (UIOs) (for 2D systems affected by disturbances) [Bisiacco, M.
      
To solve the problem of estimating an unknown input function to a linear time invariant system we propose an adaptive non-parametric method based on reversible jump Markov chain Monte Carlo (RJMCMC).
      
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Researching the characters of macro motion, numerical differentiation is introduced to describe dynamics of unknown kinematics process, then the filtering model of numerical differentiation (NDFM) and the combined filtering-predicting model of numerical differentiation (NDFPM) are constructed. Even though the dynamics of the process to be estimated is unknown, robust and simply models can be created by this approach for various applications, and it is easy to select appropriate estimation algorithms...

Researching the characters of macro motion, numerical differentiation is introduced to describe dynamics of unknown kinematics process, then the filtering model of numerical differentiation (NDFM) and the combined filtering-predicting model of numerical differentiation (NDFPM) are constructed. Even though the dynamics of the process to be estimated is unknown, robust and simply models can be created by this approach for various applications, and it is easy to select appropriate estimation algorithms for satisfied estimation quality. The states of control-system disturbed by unknown inputs are restructured by NDFM for feedback and compensating disturbances; the present-predictive estimation of kinematics parameters are captured by NDFPM for tracked object with unknown dynamics. Simulation results show that NDFM and NDFPM are robust models to obtain precise estimation.

在研究宏观空间运动特性的基础上,利用数值微分作为表达工具描述未知运动过程的动态特性,构造了数值微分型滤波模型(NDFM)和数值微分型滤波-预报联合模型(NDFPM)。这种方法能根据各种应用要求对动态特性完全未知的运动过程建立结构简单、鲁棒性强的估计模型,而且容易选择估计算法获得满意的性能。本文对未知扰动作用下的被控过程建立NDFM并实现状态重构和扰动补偿;对动态未知的被跟踪目标建立NDFPM并估计出运动参数的当前值和一步预报值。仿真结果表明这两种模型具有较强的鲁棒性和满意的估计精度。

A new image recognition algorithm—eigenspace-based approach is proposed. Firstly, recognition system obtains the possible object′s images. Then, all images and image set of each object are compressed to obtain low\|dimensional subspace, called the universal eigenspace and object eigenspace separately. Given an unknown input image, the recognition system projects the image into two kinds of eigenspace. The exact position of the projection in the eigenspace and the distribution formula of samples′ projections...

A new image recognition algorithm—eigenspace-based approach is proposed. Firstly, recognition system obtains the possible object′s images. Then, all images and image set of each object are compressed to obtain low\|dimensional subspace, called the universal eigenspace and object eigenspace separately. Given an unknown input image, the recognition system projects the image into two kinds of eigenspace. The exact position of the projection in the eigenspace and the distribution formula of samples′ projections determine the object′s species and poses in the image. Experiments are conducted using several objects with complex appearance characteristics. The results show that the proposed approach could keep robustness for the variable poses of object, and could restrain illumination variety.

提出一种基于子空间的3D目标识别方法。该方法对3D目标进行事先的训练学习,采集目标可能出现时的图像,提取场景中目标的主要特征成分,建立所有目标样本图像和每个目标样本图像对应的两类特征子空间,分别用来确定目标类型和姿态。当输入一幅未知的待识别目标图像,识别系统将其分别向两类特征空间投影,根据它在两类特征子空间中的投影位置并参照目标特征的分布规律识别目标类型和姿态。实验证明,该方法具备对目标多种姿态图像畸变的鲁棒性,对光照变化也有很好的抑制作用,取得良好的目标识别效果。

 
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