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FastGauss
- 这是改进的高斯变换的源程序，将它和粒子滤波结合起来可以降低粒子滤波的算法复杂度。
PF
- 粒子滤波的matlab源代码。在处理非高斯问题时比卡尔曼滤波强。经过测试可用。拿出来和大家分享，希望对大家有用。
pf
- 粒子滤波 目标跟踪 一维情况下 非线性非高斯
rob_hess_pf.粒子滤波现在已经成为目标跟踪领域的主流算法
- 粒子滤波现在已经成为目标跟踪领域的主流算法，它的应用范围广泛，在非线性、非高斯噪声下依然表现良好。该代码是Rob Hess 编写的。他的个人主页是：http://web.engr.oregonstate.edu/~hess/ ,Now,Partical filter has become the main algorithm in moving target tracking region.It still perform very well in nonlinear non-gaussia
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
lzlv
- 标准粒子滤波目标跟踪源码！ 一维情况下 非线性非高斯,-Standard particle filter target tracking source! One-Dimensional Non-linear non-Gaussian,
DeNosingBaseOnXiaoBo
- 一种改进的基于PCNN神经网络和QPSO粒子行为的PSO的图像滤波算法，也可以较好地去除高斯噪声-Improved PCNN-based neural network and PSO behavior QPSO particle image filtering algorithm can also be better to remove Gaussian noise
CostReference
- 一篇关于代价参考粒子滤波算法的论文，该算法的优点是不需要任何先验概率知识的假定和重采样过程，可实现并行处理。本文将代价参考粒子滤波与当前统计模型的优点相结合 ,提出一种新的当前统计模型自适应跟踪算法 ,用于非线性非高斯系统的机动目标跟踪。-A particle filter on the reference price of the paper, the advantages of the algorithm does not require any prior knowledge of the
apf-
- 关于自适应粒子滤波，我觉得很好用，贝叶斯滤波适合非线性和非高斯环境，在粒子滤波基础上 又加改进-About adaptive particle filter, I feel very good, a bayesian filter for nonlinear and non-gaussian environment, particle filter in again on the foundation and improvement
Point-target-with-Gaussion-noise
- 高斯噪声下的基于粒子滤波的雷达弱小点目标检测-Weak point particle filter-based radar target detection in Gaussian noise
code_june2010
- 多摄像机多目标跟踪算法, 具体包括混合高斯背景建模, distancemap团块映射, 粒子滤波跟踪, 匈牙利算法信息融合等.-multi camera tracking
PFtracking
- 用于目标跟踪的粒子滤波代码， 用matlab编写的，很有借鉴性，一维情况下，非高斯非线性，其中将扩展卡尔曼滤波与粒子滤波进行比较，更好的说明了粒子滤波的优越性-Particle filter for target tracking code, using matlab prepared very useful reference resistance, the one-dimensional case, the non-Gaussian nonlinear, which will be ex
850138
- 非常不错的非线性非高斯环境下的粒子滤波程序 不错的源码 很好-Very good nonlinear non-gaussian environment particle filter program source code is very good
noslinear
- 非常不错的非线性非高斯环境下的粒子滤波程序进化算法-Very good nonlinear non-gaussian environment evolution algorithm of particle filter program
587748
- 非常不错的非线性非高斯环境下的粒子滤波程序 不错的源码 很好-Very good nonlinear non-gaussian environment particle filter program source code is very good
envirmnment_algorithm
- 非常不错的非线性非高斯环境下的粒子滤波程序进化算法(Very good nonlinear non-gaussian environment evolution algorithm of particle filter program)
GPF-PHD
- 采用高斯粒子滤波实现概率假设密度算法，本人亲测效果有用