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卡尔曼滤波在数学上是一种统计估算方法，通过处理一系列带有误差的实际量测数据而得到的物理参数的最佳估算。
例如在气象应用上，根据滤波的基本思想，利用前一时刻预报误差的反馈信息及时修正预报方程，以提高下一时刻预报精度。
作温度预报一般只需要连续两个月的资料即可建立方程和递推关系。
-Kalman filter in mathematics is a statistical estimation methods, By a series of errors with the actual
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Rao-Blackwellised Particle Filters (RBPFs) are a class of Particle
Filters (PFs) that exploit conditional dependencies between
parts of the state to estimate. By doing so, RBPFs can
improve the estimation quality while also reducing the overall
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：该文把局部三值模式(Local Ternary Patterns, LTP)纹理特征引入Mean Shift 跟踪算法，提出了基于多
特征的Mean Shift 人脸跟踪算法以解决Mean shift 跟踪算法的鲁棒性问题。通过对LTP 纹理特征的分析、研究，
提出了一个LTP 关键纹理模型，既增强了目标的关键纹理信息，又简化了LTP 纹理模型。在此基础上，提出一
种基于LTP 关键纹理特征和肤色特征的Mean Shift 人脸跟踪算法，有效地解决了Mean Shift 算法的鲁棒
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本程序是关于四元数法捷联惯导解算算法的matlab程序组合包，其中包括滤波初始对准仿真，罗经法初始对准仿真，捷联惯导解算仿真，组合卡尔曼滤波等演示程序及其必需的参数矩阵转换程序，程序算法皆是本人通过大量阅读捷联惯导经典论文书籍编写的，经过调试已经通过，所得圆锥误差，划桨误差与秦永元所编惯性导航一书相符，可靠性较高。适合惯导学习者参考改进使用
-This procedure is the law about quaternion SINS algorithm matlab solver co
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The Extended Kalman Filter with profile matching
has been employed to extract road maps in satellite images.
This algorithm suffers from several drawbacks
that result in its poor performance in difficult situations.
To improve its performance
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基于多目标的跟踪和实现，里面介绍了跟踪算法的现状，以及如何基于mean shift和卡尔曼滤波改进跟踪算法-Based on multi-target tracking and realization, which describes the status of the tracking algorithm, and how mean shift and Kalman filter based tracking algorithm to improve
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基于卡尔曼算法的AR模型系数预测，利用卡尔曼滤波算法对AR模型的系数进行实时更新，可以观察到预测准确度有明显提高-Kalman algorithm based on AR model coefficients predicted using the Kalman filter AR model coefficients for real-time updates can be observed significantly improve prediction accuracy
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UKF算法及其在纯方位目标跟踪中的应用，改进 无迹卡尔曼滤波-UKF algorithm and its only target tracking application, unscented Kalman filter to improve
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无线传感器网络定位技术中可以用卡尔曼滤波来改善定位精度-the Kalman filter can be used to improve the positioning accuracy of location in wireless sensor networks
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利用kalman滤波实现GPS定位精度的提高-GPS positioning using kalman filter to improve the accuracy achieved
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卡尔曼滤波基本算法的matlab程序，最近一直在研究此类问题，程序准确无误，方便初学者学习研究，并以此为基础进行改进~-Kalman filter algorithm matlab program, has recently been in the study of such problems, the program is accurate, easy for beginners to learn research and improve as a basis to
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用多尺度卡尔曼滤波法，对信号参数进行识别估计。高频信号和低频信号识别结合起来改进了算法识别的精确度和准确度。-It is an implementation of hierarchical (a.k.a. multi-scale) Kalman filter using belief propagation. The model parameters are estimated by expectation maximization (EM) algorithm. In this impleme
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This paper presents an adaptive information fusion method to improve the
accuracy and reliability of the altitude measurement information for small unmanned aerial
rotorcraft during the landing process. Focusing on the low measurement performance
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结合kalman滤波的meanshift跟踪算法，meanshift算法是一种经典的均值漂移跟踪算法，采用颜色直方图作为跟踪特征，具有很高的稳定性和鲁棒性，kalman滤波是一种线性滤波预测算法。在meanshift算法中引入kalman滤波，可以提高算法的稳定性，同时提高算法执行效率。代码中除了avi格式视频读取采用opencv库函数外，核心算法均为纯C++实现，注释详细，很容易理解，同时具有很高的参考价值。 -Meanshift kalman filtering combined track
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This paper deals with using of low-cost Global
Navigation Satellite System (GNSS) sensors in a localization
process for an autonomous guidance system of mobile robots.
Generally, this process is made using a Kalman Filter (KF) to
fuse informa
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HSF processes the distorted image ˜ x by M filters chosen to improve the image quality for regions with different characteristics. At each pixel,
a feature vector yn is computed using local image data. The feature vector is then used to determi
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利用交互多模型无迹卡尔曼滤波算法实现机动目标跟踪。-Interacting multipl emodel Unscented kalman filter （IMM UKF)is presented to improve the performance of target tracking.
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constrained kalman filter ，这是很好的一种约束方法，对卫星很少的情况下的定位精度提高很多。-constrained kalman filter, this is a good method of a constraint on the positioning accuracy in the case of small satellites to improve a lot.
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针对感应电机扩展卡尔曼滤波器转速估计中难以取得卡尔曼滤波器系统噪声矩阵和测量噪声矩阵最优值的问题，提出了一种基于改进粒子群算法优化的扩展卡尔曼滤波器转速估计方法。算法通过融合遗传算法和粒子群算法的优点，采用可调整的算法模型对粒子群算法进行改进，将改进的粒子群算法对扩展卡尔曼滤波器中的系统噪声矩阵和测量噪声矩阵进行优化处理，将优化后的卡尔曼滤波器应用于感应电机转速估计。-
Extended K
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the code is used to the failure detection and predection of tool wear with Kalman Filter model(calculus of twice differences in order to improve better estimation precision.
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