ReBEL is a Matlabtoolkit of functions and scripts, designed to facilitate sequential Bayesian inference (estimation) in general state space models. This software consolidates research on new methods for recursive Bayesian estimation and KAlman filtering by Rudolph van der Merwe and Eric A. Wan. The code is developed and maintained by Rudolph van der Merwe at the OGI School of Science & Engineering at OHSU (Oregon Health & Science University).
标签： Matlabtoolkit facilitate sequential functions
上传时间： 2015-08-31
上传用户：皇族传媒
This paper deals with the problem of speech enhancement when a corrupted speech signal with an additive colored noise is the only information available for processing. KAlman filtering is known as an effective speech enhancement technique, in which speech signal is usually modeled as autoregressive (AR) process and represented in the state-space domain.
标签： speech with enhancement corrupted
上传时间： 2015-09-07
上传用户：zhangyi99104144
This paper deals with the problem of speech enhancement when only a corrupted speech signal is available for processing. KAlman filtering is known as an effective speech enhancement technique, in which speech signal is usually modeled as autoregressive (AR) model and represented in the state-space domain.
标签： speech enhancement corrupted problem
上传时间： 2013-12-20
上传用户：569342831
Klaas Gadeyne, a Ph.D. student in the Mechanical Engineering Robotics Research Group at K.U.Leuven, has developed a C++ Bayesian Filtering Library that includes software for Sequential Monte Carlo methods, KAlman filters, particle filters, etc.
标签： Engineering Mechanical Robotics Research
上传时间： 2015-09-07
上传用户：Altman
这是一个不错运动目标检测的方案，涉及到帧间差分法和KAlman滤波器
上传时间： 2013-12-25
上传用户：1583060504
该软件是我读硕士的时候写的，它可以对测井曲线进行直方图、小波变换，曲线拉伸、均值绿波、中值滤波、KAlman滤波以及插值等等操作，程序里还包含了神经网络的内容，非常丰富，是您学习VC++编程和数据处理的好资料！绝对超值！ 请先阅读文件夹下的read me 文件
上传时间： 2013-12-08
上传用户：风之骄子
机动目标的跟踪问题一直是人们研究的重点，实现机动目标精确跟踪，首要解决的问题就是使所建立的目标运动模型与实际的目标运动模型匹配。目前常用的有多模型(MM)，交互式多模型(IMM)，切换模型等。多模型方法就是对一组具有不同机动模型分别进行KAlman滤波，最终的参数估计是各滤波器估计值的加权和；在多模型基础上，Shalom提出了交互式多模型方法，这一方法对无序目标的机动检测，显示了更好的鲁棒性和跟踪的稳定性；切换模型则是分别建立机动和非机动运动模型，利用机动检测实现在这两个模型之间的切换。一般来说，交互式多模型的跟踪性能较好。
标签： 机动
上传时间： 2013-12-14
上传用户：maizezhen
在matlab环境下，实现KAlman滤波器跟踪目标。
上传时间： 2013-12-13
上传用户：gououo
一片介绍双估计的很好的文章。同时估计动态系统的状态和模型参数，使用扩展KAlman filter和ukf方法，很有参考价值
上传时间： 2015-11-25
上传用户：ippler8
惯性导航和GPS的数据融合，基于模糊自适应KAlman滤波的方法
上传时间： 2014-01-24
上传用户：chens000
