Description: 基于次优贝叶斯估计的非线形非高斯条件下的粒子滤波器的MATELAB仿真-based Bayesian estimation of non-linear non-Gaussian under the conditions of the particle filter simulation MATELAB Platform: |
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Author:husheng |
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Description: this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.-this demo is to show you how to implement a ge neric SIR (a.k.a. particle, the bootstrap. Monte Carlo) filter to estimate the hidden stat es of a nonlinear. non-Gaussian state space model. Platform: |
Size: 6144 |
Author:大辉 |
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Description: The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.-The software implements particle filteri Vi and Rao Blackwellised particle filtering az r conditionally Gaussian Models. The RB algori thm can be interpreted as an efficient stochast ic mixture of Kalman filters. The software also includes efficient state-of-the-art resampl ing routines. These are generic and suitable az r any application. Platform: |
Size: 130048 |
Author:大辉 |
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Description: 非常不错的非线性非高斯环境下的粒子滤波程序-very good nonlinear non-Gaussian environment under the particle filter process Platform: |
Size: 8192 |
Author:侯睿 |
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Description: 基本粒子滤波器的实现,对非线性非高斯目标可进行有效跟踪!-elementary particle filter to the realization of non-Gaussian nonlinear objectives can be effectively tracking! Platform: |
Size: 1024 |
Author:wyb |
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Description: 本文的题目是改进的粒子滤波在组合导航中的应用研究。文档可用caj打开。
本课题首先研究了GPS/DR车载定位系统的组合模型，然后在分析了非线性滤波的基础上，引入了粒子滤波。粒子滤波是一种基于递推计算的序列蒙特卡罗算法，它采用一组从概率密度函数上随机抽取的并附带相关权值的粒子集来逼近后验概率密度，从而不受非线性、非高斯问题的限制。虽然粒子滤波存在诸多优点，然而它仍然存在诸如粒子数匿乏、滤波性能不高、实时性差等问题。-The title of this article is to improve the particle filter in the navigation of the applied research. CAJ can be used to open the document. This issue initially on the GPS/DR Vehicle Location System portfolio model, and then the analysis of nonlinear filtering based on the introduction of a particle filter. Particle filter is a recursive calculation based on Sequential Monte Carlo algorithm, it uses a set of probability density function from random samples and weights attached to the relevant set of particles to approximate a posteriori probability density, and thus not subject to non-linear, the issue of non-Gaussian constraints. Although there are many advantages of particle filter, yet it still exists, such as particle number Punic poor, filter performance is not high, real-time poor. Platform: |
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Author:阳关 |
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Description: 学位论文；运动物体跟踪方法主要包括卡尔曼滤波，Mean-shift，Camshifi算法，粒子滤波器，Snake模型等；应用卡尔曼滤波方法设计了一套煤矿矿工出入自动监测系统；提出了一种新的基于高斯混合模型的颜色特征提取方法，该方法克服了现有的Camshift算法Continuousl y Adaptive eanshift中跟踪目标特征提取精确度低和计算复杂度高的缺陷-Dissertation moving object tracking methods include Kalman filtering, Mean-shift, Camshifi algorithm, particle filter, Snake model the application of Kalman filtering method designed a coal miners out of automatic monitoring system a new Gaussian mixture model based on the color feature extraction method to overcome the existing Camshift algorithm Continuousl y Adaptive eanshift track target feature extraction accuracy and low computational complexity and high defects Platform: |
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Author:田卉 |
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Description: "A Tutorial on Particle Filters for Online Nonlinear Non-Gaussian Bayesian Tracking"
This is a paper about tracking by particle filter.
This is very useful. Platform: |
Size: 330752 |
Author:Wolf |
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Description: 粒子滤波技术在非线性、非高斯系统表现出来的优越性，决定了它的应用范围非常广泛。另外，粒子滤波器的多模态处理能力，也是它应用广泛有原因之一。国际上，粒子滤波已被应用于各个领域。在经济学领域，它被应用在经济数据预测；在军事领域已经被应用于雷达跟踪空中飞行物，空对空、空对地的被动式跟踪；在交通管制领域它被应用在对车或人视频监控；它还用于机器人的全局定位。
-Particle filter technology in the non-linear, non-Gaussian system demonstrated the superiority of the decision of its wide range of applications. In addition, the particle filter for multimodal capabilities, also has one of the reasons it is widely used. Internationally, the particle filter has been applied to various fields. In economics, it is applied to forecast economic data in the military field have been applied to radar tracking aerial flying objects, air to air, air-passive tracking in the field of traffic control it was used in the car or the person video monitoring also used the global positioning robot. Platform: |
Size: 346112 |
Author:fanlianxiang |
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Description: 本系统中VIS欠缺的SIFT_VC.lib文件。。。
http://www.pudn.com/downloads224/sourcecode/math/detail1055031.html-This is lib file, which is used in Video Intelligent System (VIS) based on the Microsoft Visual Studio 2008 compiler environment and OpenCV 2.0 library. It includes foreground detection, motion object detection, motion object tracking, trajectories generation and analysis modules. It realizes a friendly interface based on dialog, which provides a convenient example for new learners.
keywords: opencv, mixture of gaussian model, sift feature and ransac method, mean shift, particle filter, kalman filter, object detection and tracking, video intelligent system. Platform: |
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Author: |
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Description: 利用高斯算法的粒子滤波器，可以应用于机器人自主定位等应用-Gaussian particle filter algorithm can be used in applications such as robot self-localization Platform: |
Size: 73728 |
Author:程鹏 |
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Description: 粒子滤波是基于递推的MonteCarlo仿真方法的总称, 原则上可用于任意非线性、非高斯随机系统的状态估计。-Particle filter is based on the the MonteCarlo simulation method of recursive general principle can be used for any nonlinear, non-Gaussian random system state estimation. Platform: |
Size: 223232 |
Author:冯浩 |
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Description: 粒子滤波是基于递推的蒙特卡罗模拟方法的总称，可用于任意非线性，非高斯随机系统的状态估计。-The particle filter is based on recursive Monte Carlo simulation method general, can be used for any non-linear, non-Gaussian random system state estimation. Platform: |
Size: 339968 |
Author:冯浩 |
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Description: 粒子滤波算法，通过此程序，可以成功的仿真出粒子滤波。在滤波过程中粒子滤波可以处理任意形式的概率，而不像Kalman滤波只能处理高斯分布的概率问题。他的一大优势也在于此。 -Particle filter, through this program, you can emulate the success of the particle filter. In the process of filtering particle filter can handle any form of probabilities, rather than the Kalman filter can only handle a Gaussian probability distribution. He s a big advantage this. Platform: |
Size: 16384 |
Author:刘龙 |
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