Description: kalman 滤波的介绍文档，很基本，可以参考参考的-Kalman filtering introductory documentation, very basic, they can refer to the reference Platform: |
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Author:方锐 |
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Description: ：介绍了扩展卡尔曼滤波算法和无迹变换(unscented transformation，UT)算法，并对扩展卡尔曼滤波算法(EKF)和无
迹卡尔曼滤波算法(UKF)进行比较，阐明了UKF优于EKF。在此基础上，提出了一种基于Unscented变换(uT)的高斯和滤
波算法，该算法首先通过合并准则得到适当个数的混合高斯模型，逼近系统中非高斯噪声的概率密度-: Introduction of the extended Kalman filter algorithm and unscented transform (unscented transformation, UT) algorithm, the extended Kalman filter algorithm (EKF) and unscented Kalman filter (UKF) for comparison to clarify the UKF is superior to EKF. On this basis, we propose an approach based on Unscented Transform (uT) and the Gaussian filtering algorithm, which first of all, by merging the appropriate number of criteria to be a mixture of Gaussian model, which was close to the system of the Central African Gaussian noise probability density Platform: |
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Description: kalman 滤波英文论文,题目为
An Introduction to the Kalman Filter-Kalman Filter English guid
An Introduction to the Kalman Filter Platform: |
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Author:gaolang |
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Description: 1．什么是卡尔曼滤波器（What is the Kalman Filter?）
2．卡尔曼滤波器的介绍（Introduction to the Kalman Filter）
3．卡尔曼滤波器算法（The Kalman Filter Algorithm）
4．简单例子（A Simple Example）
5. 用matlab做的kalman滤波程序,已通过测试
还有下面一个 Matlab源程序，显示效果更好。
-1. What is a Kalman filter
2. Introduction to the Kalman Filter
3. The Kalman Filter Algorithm
4. A Simple Example
5. Kalman filter code with matlab, has been tested.Another Matlab code shows better. Platform: |
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Author:新鹏 |
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Description: 卡尔曼滤波简单例程，一维情况。An Introduction to Kalman Filter中的例子。-Kalman filter is simple routines, one-dimensional situation. An Introduction to Kalman Filter in the example. Platform: |
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Description: An Introduction to the Kalman Filter. Greg Welch and Gary Bishop. Department of Computer Science, University of North Carolina at Chapel Hill.
Updated: Monday, July 24, 2006.-An Introduction to the Kalman Filter. Greg Welch and Gary Bishop. Department of Computer Science, University of North Carolina at Chapel Hill.
Updated: Monday, July 24, 2006. Platform: |
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Author:rodralez |
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Description: KALMANF - updates a system state vector estimate based upon an
observation, using a discrete Kalman filter.
Version 1.0, June 30, 2004
This tutorial function was written by Michael C. Kleder
INTRODUCTION
Many people have heard of Kalman filtering, but regard the topic
as mysterious. While it s true that deriving the Kalman filter and
proving mathematically that it is "optimal" under a variety of
circumstances can be rather intense, applying the filter to
a basic linear system is actually very easy. This Matlab file is
intended to demonstrate that.
An excellent paper on Kalman filtering at the introductory level,
without detailing the mathematical underpinnings, is:
"An Introduction to the Kalman Filter"
Greg Welch and Gary Bishop, University of North Carolina- KALMANF - updates a system state vector estimate based upon an
observation, using a discrete Kalman filter.
Version 1.0, June 30, 2004
This tutorial function was written by Michael C. Kleder
INTRODUCTION
Many people have heard of Kalman filtering, but regard the topic
as mysterious. While it s true that deriving the Kalman filter and
proving mathematically that it is "optimal" under a variety of
circumstances can be rather intense, applying the filter to
a basic linear system is actually very easy. This Matlab file is
intended to demonstrate that.
An excellent paper on Kalman filtering at the introductory level,
without detailing the mathematical underpinnings, is:
"An Introduction to the Kalman Filter"
Greg Welch and Gary Bishop, University of North Carolina Platform: |
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Author:mabaiwang |
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Description: In putting together this course pack we decided not to simply include copies of the slides
for the course presentation, but to attempt to put together a small booklet of information
that could stand by itself. The course slides and other useful information, including a new
Java-based Kalman Filter Learning Tool are available at
http://www.cs.unc.edu/~tracker/ref/s2001/kalman/
In addition, we maintain a popular web site dedicated to the Kalman fi lter. This site
contains links to related work, papers, books, and even some software.
http://www.cs.unc.edu/~welch/kalman/
We expect that you (the reader) have a basic mathematical background, suffi cient to
understand explanations involving basic linear algebra, statistics, and random signals.
-In putting together this course pack we decided not to simply include copies of the slides
for the course presentation, but to attempt to put together a small booklet of information
that could stand by itself. The course slides and other useful information, including a new
Java-based Kalman Filter Learning Tool are available at
http://www.cs.unc.edu/~tracker/ref/s2001/kalman/
In addition, we maintain a popular web site dedicated to the Kalman fi lter. This site
contains links to related work, papers, books, and even some software.
http://www.cs.unc.edu/~welch/kalman/
We expect that you (the reader) have a basic mathematical background, suffi cient to
understand explanations involving basic linear algebra, statistics, and random signals.
Platform: |
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Author:ele rock |
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Description: kalman 滤波器使用介绍，初学者的参考,最好先学习一下其推到过程-kalman filter using the introduction of reference for beginners, it is best to first learn about the process of pushing Platform: |
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Author:张汉 |
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Description: 卡尔曼滤波器概论，学习的入门材料，初学者可以看看。-An Introduction to the Kalman Filter is very good conference,which is commended to the students. Platform: |
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Author:武拥军 |
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Description: Kalman Filter（一种有用的滤波器）介绍，包括数学推导和基本的概念。-An introduction to Kalman filter, which is an very useful tool to filter noise Platform: |
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Author:邵帅 |
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Description: 卡尔曼滤波原理及应用—MATLAB仿真主要介绍数字信号处理中的卡尔曼（Kalman）滤波算法及在相关领域应用。全书共7章。第1章为绪论。第2章介绍MATLAB算法仿真的编程基础。第3章介绍线性Kalman滤波。第4章讨论扩展Kalman滤波，并介绍其在目标跟踪和制导领域的应用和算法仿真。第5章介绍UKF滤波算法，同时也给出其应用领域内的算法仿真实例。第6章介绍了交互多模型Kalman滤波算法。第7章介绍Simulink环境下，如何通过模块库和S函数构建Kalman滤波器，并给出了系统是线性和非线性两种情况的滤波器设计方法(Principle and Application of Kalman Filter - MATLAB simulation mainly introduces Kalman filtering algorithm in digital signal processing and its application in related fields. The book consists of 7 chapters. The first chapter is the introduction. The second chapter introduces the programming foundation of MATLAB algorithm simulation. The third chapter introduces linear Kalman filtering. Chapter 4 discusses the extended Kalman filter, and introduces its application and algorithm simulation in the field of target tracking and guidance. The fifth chapter introduces the UKF filtering algorithm, and gives an example of algorithm simulation in its application area. The sixth chapter introduces the interacting multiple model Kalman filtering algorithm. Chapter 7 introduces how to construct Kalman filter by module library and S-function in Simulink environment, and gives the design method of Kalman filter for both linear and nonlinear systems.) Platform: |
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Author:jianjian健健 |
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