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opencv运动检测
- 本程序实现了基于OPenCV的运动检测，并且应用了各种滤波方法，比如卡尔曼滤波和粒子滤波，及小波变换等，开发平台：VC6.0，简单易懂。已经过调试，可直接执行。适合图像处理、运动控制等专业的入门人士进行学习。
particale_filters
- 粒子滤波器是通过蒙特卡罗模拟来实现递归贝叶斯滤波，它不需要线性、高斯噪声的假设，适用于任何能用状态空间模型表示的非线性系统，比卡尔曼滤波器的适用范围广。这里给出了几个粒子滤波的matlab编程实例。-Particle filters are using Monte Carlo simulations to achieve the recursive Bayesian filtering, it does not require linear, Gaussian noise assumptions
PF-EKF
- 粒子滤波和扩展卡尔曼滤波的对比分析，matlab算法，欢迎交流-Particle filter and comparative analysis of the extended Kalman filter, matlab algorithm, welcomed the exchange of
kalmansourcecode
- 使用matlab_GUI编写，包括：扩展卡尔曼滤波，粒子滤波，去偏卡尔曼滤波和循环增益尔曼滤波的源程序，根据初始预测计算滤波值 再通过输入观测值进行卡尔曼滤波的仿真GUI界面程序-Matlab_GUI prepared to use, including: extended Kalman filter, particle filter, to the partial gain of Kalman filter and recycling thalmann source filter, acc
EKF_PF
- 扩展卡尔曼滤波与粒子滤波 性能比较的源程序-Extended Kalman filter and particle filter source
SequentialTracking
- 非常好的粒子滤波程序:扩展卡尔曼模型下的序列追踪-very good particle filter : Extended Kalman model tracing the sequence
zuijinlinyu
- 本程序通过卡尔曼滤波。对航迹进行估计， 然后通过最近邻域算法，实现数据互联。-the procedure Kalman filter. Estimate right track, and then through the recent neighborhood algorithm, data Internet.
ekf_pf
- 基于卡尔曼滤波和粒子滤波器级联模型的静基座惯导初始对准算法及仿真-Based on the Kalman filter and particle filter cascade model static base INS initial alignment algorithm and simulation
ParticleEx1
- 扩展卡尔曼滤波与粒子滤波的比较，对某复杂函数曲线的跟踪。-Extended Kalman filter and particle filter compared to the complexity of a function curve tracking.
OnTrackingofMovingObjects
- 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 filt
teacherstudent
- 粒子滤波在无线传感器网络中的应用，与卡尔曼滤波相比较，具有优势。-Particle filter in the wireless sensor network applications, compared with the Kalman filter, has an advantage.
KFandPF
- 卡尔曼滤波器和粒子滤波器的MATLAB演示程序-Kalman filters and particle filters MATLAB demo
bailey02thesis
- 一篇应用卡尔曼滤波和粒子滤波进行移动机器人室外定位的博士论文-A PhD Thesis Mobile Robot Localisation and Mapping in Extensive Outdoor Environments Utilizing Kalman Filter and Particle Filter
PFmatlab
- 自己收集的粒子滤波程序，包括基本的程序，卡尔曼滤波以及改进的算法。-Their own procedures for the collection of the particle filter.
work
- 本程序是基于机动目标跟踪课题的整个算法程序，其中包括卡尔曼，扩展卡尔曼和粒子滤波程序及其仿真代码和仿真的图形。-This procedure is based on the subject of maneuvering target tracking algorithm for the whole procedure, including Kalman, extended Kalman and particle filter process and its simulation code and
EKFPFdemo
- 该程序实现的是扩展卡尔曼粒子滤波，即采用扩展卡尔曼滤波得到粒子滤波的建议分布，粒子滤波再从其中采样进行滤波。-The program implementation is the extended Kalman particle filter, that is, extended Kalman filter using the particle filter proposal distribution, the particle filter and then is filtered from o
ParticleEx1
- 粒子滤波算法与扩展卡尔曼滤波算法的比较方法。-Particle filter and extended Kalman filter algorithm for comparison.
The_nonlinear_filtering_algorithm_performance_anal
- 对目前非线性滤波的主要算法即扩展卡尔曼滤波、不敏卡尔曼滤波、粒子滤波、扩展卡尔曼粒子滤波和不敏粒子滤波的滤波模型、适用条件、性能进行了分析比较，给出了每种方法的计算复杂度．通过一个非线性非高斯模型进行了仿真，验证了这些算法的性能。-Present the main algorithms of the nonlinear filtering extended Kalman filter, Unscented Kalman filter, particle filter, particle filt
UPF
- 无迹卡尔曼粒子滤波，有效的估计状态,ZHENHAO YONG(An unscented Calman particle filter is used to estimate the state effectively)
example3_7 粒子滤波与扩展卡尔曼滤波对比
- 用于进行粒子滤波和联合卡尔曼滤波进行对比(For particle filter and federated Kalman filter comparison)