Description: 卡尔曼滤波是一种高效率的递归滤波器(自回归滤波器), 它能够从一系列的不完全包含噪声的测量(英文:measurement)中，估计动态系统的状态。 -Kalman Filter is a highly efficient recursive filter (autoregressive filter), It can complete a series of noise measurements included (in English : measurement). Dynamic System estimated the state. Platform: |
Size: 1734 |
Author:秦露妮 |
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Description: 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.-This paper deals with the problem of speech enhancement when a corrupted speech signal wit h an additive colored noise is the only informat ion available for processing. Kalman filterin g is known as an effective speech enhancement te chnique. in which speech signal is usually modeled as aut oregressive (AR) process and represented in th e state-space domain. Platform: |
Size: 102400 |
Author:rifer |
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Description: 卡尔曼滤波是一种高效率的递归滤波器(自回归滤波器), 它能够从一系列的不完全包含噪声的测量(英文:measurement)中，估计动态系统的状态。 -Kalman Filter is a highly efficient recursive filter (autoregressive filter), It can complete a series of noise measurements included (in English : measurement). Dynamic System estimated the state. Platform: |
Size: 1024 |
Author:秦露妮 |
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Description: kalman滤波器的C源代码，kalman滤波器的用途很广，比如卡尔曼滤波是一种高效率的递归滤波器(自回归滤波器), 它能够从一系列的不完全包含噪声的测量，估计动态系统的状态。-kalman filter C source code, kalman filter uses a very wide, such as the Kalman filter is an efficient recursive filter (autoregressive filter), it can not completely contain a series of noise measurements, estimated dynamic system state. Platform: |
Size: 1024 |
Author:taofen |
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Description: 卡尔曼滤波算法实现代码.卡尔曼滤波是一种高效率的递归滤波器[自回归滤波器], 它能够从一系列的不完全及包含噪声的测量[英文:measurement]中，估计动态系统的状态。-Kalman filter algorithm implementation code. Kalman filter is an efficient recursive filter [autoregressive filter], it can from a series of incomplete and contains noise measurement [English: measurement], the estimated dynamic system state. Platform: |
Size: 13312 |
Author:sunxm |
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Description: 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。他的广泛应用已经超过30年，包括机器人导航，控制，传感器数据融合甚至在军事方面的雷达系统以及导弹追踪等等。近年来更被应用于计算机图像处理，例如头脸识别，图像分割，图像边缘检测等等。-Kalman filter is an " optimal recursive data processing algorithm (optimal autoregressive data-processing algorithm)." To address the very most of the questions, he is the best, most efficient, if not the most useful. He has been widely used for more than 30 years, including robot navigation, control, sensor data fusion and even in military radar systems and missile tracking and so on. Recent years been applied to computer image processing, such as头脸recognition, image segmentation, image edge detection and so on. Platform: |
Size: 570368 |
Author:曲晓川 |
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Description: 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。-Kalman filter is an " optimal recursive data processing algorithm (autoregressive to optimize data-processing algorithm)." To address the very most, he is the best, most efficient, if not the most useful. Platform: |
Size: 414720 |
Author:jessic |
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Description: 简单来说，卡尔曼滤波器是一个"optimal recursive data processing algorithm（最优化自回归数据处理算法）"。对于解决很大部分的问题，他是最优，效率最高甚至是最有用的。-In short, the Kalman filter is an " optimal recursive data processing algorithm (optimal autoregressive data processing algorithm)." For most of the problems to solve it, he is the best, most efficient or even useful. Platform: |
Size: 416768 |
Author:yang |
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Description: 卡尔曼滤波是一种高效率的递归滤波器(自回归滤波器), 它能够从一系列的不完全包含噪声的测量(英文:measurement)中，估计动态系统的状态。本程序实现了基于kalman的目标跟踪。-Kalman filter is an efficient recursive filter (autoregressive filter), it can not completely contain from a series of noise measurements (in English: measurement), the estimated dynamical systems. Based on the Program for target tracking kalman. Platform: |
Size: 2048 |
Author:sunny |
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Description: 卡尔曼滤波是一种高效率的递归滤波器(自回归滤波器), 它能够从一系列的不完全包含噪声的测量中，估计动态系统的状态。-Kalman filter is an efficient recursive filter (autoregressive filter), it can not completely contain from a series of noise measurements, the estimated dynamical systems. Platform: |
Size: 270336 |
Author:machinery |
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Description: 卡尔曼滤波是一种高效率的递归滤波器(自回归滤波器), 它能够从一系列的不完全包含噪声的测量(英文:measurement)中，估计动态系统的状态。-Kalman filter is an efficient recursive filter (autoregressive filter), which can contain from a series of incomplete measurement of noise (in English: measurement) is estimated dynamic system state. Platform: |
Size: 1024 |
Author:马晓敏 |
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Description: Calculates adaptive autoregressive (AAR) and adaptive autoregressive moving average estimates (AARMA) of real-valued data series using Kalman filter algorithm.
REFERENCE:
A. Schloegl (2000), The electroencephalogram and the adaptive autoregressive model: theory and applications.ISBN 3-8265-7640-3 Shaker Verlag, Aachen, Germany. Platform: |
Size: 3072 |
Author:Pubo |
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Description: 卡尔曼滤波C程序源码 卡尔曼滤波器是一个“optimal recursive data processing algorithm（最优化自回归数据处理算法）”。对于解决非常大部分的问题，他是最优，效率率最高甚甚至是最有用的。他的广泛应用已经超过30年，包含机器人导航，控制，传感器数据融合甚至在军事方面的雷达系统和导弹追踪等等。近年来更被应用于计算机图像处理，例如头脸识别，图像分割，图像边缘检测等等。
-C program source code of Kalman filter Kalman filter is an optimal recursive data processing algorithm (optimized the the autoregressive data processing algorithm) " . To solve the very most of the problems, he is the best, the efficiency of the highest rates of very even be the most useful. He' s widely used for more than 30 years, including robot navigation and control, and sensor data fusion even in the military radar system and missile tracking. In recent years, used in computer image processing, such as the head and face recognition, image segmentation, image edge detection. Platform: |
Size: 1024 |
Author:xinlnix |
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Description: This paper deals with using of low-cost Global
Navigation Satellite System (GNSS) sensors in a localization
process for an autonomous guidance system of mobile robots.
Generally, this process is made using a Kalman Filter (KF) to
fuse information coming from different sensors. But as GNSS
error is an unpredictable stochastiscal process, the localization
estimated by the KF becomes unreliable. To solve this problem,
the error of a cheap GNSS receiver is analyzed. Then, an
AutoRegressive process (AR process) is used to establish a reliable
prediction model. A second problem of GNSS systems concerns
the disturbances in the observation of satellites. To detect this
disturbance, we use a condition based on the Mahalanobis
distance. This model and condition are taken into account in
the localization system to improve its Platform: |
Size: 344064 |
Author:hassan |
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Description: The code allows to estimate the Clarck model by maximum likelihood. It is assumed that the series has 2 unobservable components: a trend and a cycle. In the case of the trend, an autoregressive process of order 2 is assumed and for the case of the cycle a random walk is assumed. An example is made with the data of Peru Platform: |
Size: 1604 |
Author:franciscososasotomayor123 |
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