Description: 非线性滤波在数字图像处理中的应用。 -nonlinear filtering in the digital image processing applications. Non-linear filtering in the digital image processing applications. Platform: |
Size: 53156 |
Author:fay |
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Description: 工学博士学位论文
目前，扩展卡尔曼滤波是研究初始对准和惯性/GPS组合导航问题的一个主要手段。
但初始对准和惯性/GPS组合导航问题本质上是非线性的，对模型进行线性化的扩展卡
尔曼滤波在一定程度上影响了系统的性能。近年来，直接使用非线性模型的
UKF(Unscented Kalman Filtering, UKF)和粒子滤波，正在逐渐成为研究非线性估计问题
的热点和有效方法。
本文研究了UKF和粒子滤波两种非线性滤波方法，并将其应用于非线性静基座对
准和惯性/GPS组合导航，系统地研究了初始对准和惯性/GPS组合导航中各种非线性项-Engineering PhD thesis Currently, EKF is the initial alignment study and inertial / GPS navigation of a major means. However, initial alignment and inertial / GPS navigation on the nature of the problem is nonlinear. on the model of linear expansion of the Kalman filter certain extent affected the performance of the system. In recent years, direct use of the non-linear model (UKF Unscented Kalman Filtering. UKF) and the particle filter, is gradually becoming nonlinear estimation of the hot and effective method. This paper studies the UKF and particle filter both nonlinear filtering method, will be applied to nonlinear static Base Alignment and inertial / GPS navigation, systematic study of initial alignment and inertial / GPS navigation various nonlinear term Platform: |
Size: 5070259 |
Author:daniel |
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Description: 非线性滤波除噪技术综述 中值 均值 还有自适应技术的区别-nonlinear filtering in addition to noise Technology Value adaptive technology also mean the difference between Platform: |
Size: 64759 |
Author:lele |
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Description: 一篇描述非线性滤波的经典文章，推荐给大家，文中有程序的介绍。-a description of the classical nonlinear filtering articles, recommended to you the text of the procedures introduced. Platform: |
Size: 945086 |
Author:王力 |
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Description: 非线性滤波在数字图像处理中的应用。 -nonlinear filtering in the digital image processing applications. Non-linear filtering in the digital image processing applications. Platform: |
Size: 53248 |
Author:fay |
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Description: 卡尔曼滤波方面的文章，非常不错，很值得一看-Kalman filtering aspects of the article, very good, it is worth a visit Platform: |
Size: 188416 |
Author:Arthur |
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Description: This book presents a comprehensive and unifying introduction to kernel adaptive fi ltering. Adaptive signal processing theory has been built on three pillars: the linear model, the mean square cost, and the adaptive least - square learning algorithm. When nonlinear models are required, the simplicity of linear adaptive fi lters evaporates and a designer has to deal with function approximation, neural networks, local minima, regularization, and so on. Is this the only way to go beyond the linear solution? Perhaps there is an alternative, which is the focus of this book. The basic concept is to perform adaptive fi ltering in a linear space that is related nonlinearly to the original input space. If this is possible, then all three pillars and our intuition about linear models can still be of use, and we end up implementing nonlinear fi lters in the input space. - This book presents a comprehensive and unifying introduction to kernel adaptive fi ltering. Adaptive signal processing theory has been built on three pillars: the linear model, the mean square cost, and the adaptive least - square learning algorithm. When nonlinear models are required, the simplicity of linear adaptive fi lters evaporates and a designer has to deal with function approximation, neural networks, local minima, regularization, and so on. Is this the only way to go beyond the linear solution? Perhaps there is an alternative, which is the focus of this book. The basic concept is to perform adaptive fi ltering in a linear space that is related nonlinearly to the original input space. If this is possible, then all three pillars and our intuition about linear models can still be of use, and we end up implementing nonlinear fi lters in the input space. Platform: |
Size: 1442816 |
Author:johnny |
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Description: 这本书提供了坚实的介绍卡尔曼滤波的理论和实践方面的读者。它已经更新了卡尔曼滤波，包括适应非线性滤波，更可靠的平滑方法，并在导航应用程序开发的实施和应用的最新发展。所有的软件是在MATLAB中，提供给读者的机会，发现如何卡尔曼滤波行动，并考虑实际运算需要保持结果的准确性。-This book provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. It has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results. Platform: |
Size: 3176448 |
Author:luaw2006 |
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Description: This book provides readers with a solid introduction to the theoretical and practical aspects of Kalman filtering. It has been updated with the latest developments in the implementation and application of Kalman filtering, including adaptations for nonlinear filtering, more robust smoothing methods, and developing applications in navigation. All software is provided in MATLAB, giving readers the opportunity to discover how the Kalman filter works in action and to consider the practical arithmetic needed to preserve the accuracy of results. Platform: |
Size: 3177472 |
Author:anna |
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Description: 主要实现几种非线性滤波算法的比较，编程平台为VS2012，界面使用了Windows GDI实现，仅包含可执行程序与说明文档，代码暂未上传（代码最早在三个月后上传），下载前请看清说明。-This is an excutive file for validating some tyical nonlinear filtering algorithms. Please note that the original codes are excluded, which will be uploaded in three months. Platform: |
Size: 2732032 |
Author:小新 |
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Description: 非线性滤波的程序，里面包含扩展卡尔曼滤波和无迹卡尔曼滤波滤波，可应用于很多非线性系统-Nonlinear filtering process, which includes extended Kalman filter and unscented Kalman filter filtering can be applied to many nonlinear system Platform: |
Size: 126976 |
Author:natsumezao |
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Description: In this paper we develop and analyze real-time and
accurate filters for nonlinear filtering problems based on the
Gaussian distributions. We present the systematic formulation
of Gaussian filters and develop efficient and accurate numerical
integration of the optimal filter. We also discuss the mixed
Gaussian filters in which the conditional probability density
is approximated by the sum of Gaussian distributions. A new
update rule of weights for Gaussian sum filters is proposed.
Our numerical testings demonstrate that new filters significantly
improve the extended Kalman filter with no additional cost and
the new Gaussian sum filter has a nearly optimal performance Platform: |
Size: 414720 |
Author:Gomaa Haroun |
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Description: Kernel自适应滤波器算法是基于Kernels的在线自适应回归算法。非常适合非线性滤波，跟踪和回归。该工具箱包括算法，演示和性能比较工具(Kernel adaptive filtering algorithms are online and adaptive regression algorithms based on kernels. They are suitable for nonlinear filtering, prediction, tracking and nonlinear regression in general. This toolbox includes algorithms, demos, and tools to compare their performance.) Platform: |
Size: 357376 |
Author:yjch |
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