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[Mathimatics-Numerical algorithmsKalman estimater

Description: kalman估值器,为了简洁未使用矩阵计算,应用了kalman滤波,c语言实现-A kalman estimator written with c , without matrix operation,applied kalman filter.
Platform: | Size: 2021 | Author: mikefun | Hits:

[Other resourceAnadaptivefilteringapproachtotargettracking

Description: A method is presented for augmenting an extended Kalman filter with an adaptive element. The resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics.-A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics .
Platform: | Size: 339059 | Author: rifer | Hits:

[Mathimatics-Numerical algorithmsKalman estimater

Description: kalman估值器,为了简洁未使用矩阵计算,应用了kalman滤波,c语言实现-A kalman estimator written with c , without matrix operation,applied kalman filter.
Platform: | Size: 2048 | Author: | Hits:

[Industry researchAnadaptivefilteringapproachtotargettracking

Description: A method is presented for augmenting an extended Kalman filter with an adaptive element. The resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics.-A method is presented for augmenting an ext Kalman ended with an adaptive filter element. T he resulting estimator provides robustness to parameter uncertainty and unmodeled dynamics .
Platform: | Size: 338944 | Author: rifer | Hits:

[Algorithmkalmanfilters

Description: A Kalman filter is a stochastic , recursive estimator , which estimates the state of a system based on the knowledge of the system input, the measurement of the system output, and a model of the relation between input and output.
Platform: | Size: 169984 | Author: yag | Hits:

[AlgorithmKalmanFilterwiki

Description: The Kalman filter30 is a minimum-variance filter in which time-series measurements are incorporated recursively into estimates of state variables it is the optimal, Bayesian least-squares estimator for linear dynamic systems.-text
Platform: | Size: 265216 | Author: 刘海海 | Hits:

[AlgorithmRoweis_199NeuralComputation

Description: The Kalman filter30 is a minimum-variance filter in which time-series measurements are incorporated recursively into estimates of state variables it is the optimal, Bayesian least-squares estimator for linear dynamic systems.-The Kalman filter30 is a minimum-variance filter in which time-series measurements are incorporated recursively into estimates of state variables it is the optimal, Bayesian least-squares estimator for linear dynamic systems.
Platform: | Size: 202752 | Author: 刘海海 | Hits:

[Successful incentiveWelch_2006_Filter

Description: The Kalman filter30 is a minimum-variance filter in which time-series measurements are incorporated recursively into estimates of state variables it is the optimal, Bayesian least-squares estimator for linear dynamic systems.-dd
Platform: | Size: 158720 | Author: 刘海海 | Hits:

[matlabkalman_1

Description: Kalman parameter estimator source code. Kalman is used a parameter estimator here. By using that algorithm one can estimate the expected value and variance of random variable.
Platform: | Size: 1024 | Author: osman | Hits:

[matlabkalman

Description: kalman filter estimator
Platform: | Size: 1024 | Author: Joony | Hits:

[AI-NN-PR4floorearthquake

Description: 近年来,随着各国大地震的接连发生,对人类的生命财产造成了巨大的损失,高层建筑的隔震抗震引起了广泛关注。因此,在实际结构中对与建筑隔震性能的研究具有重要的意义。本文提出依次采用扩展卡尔曼识别结构响应和最小二乘识别未知激励的方法,对隔震层的无模型非线性特性进行识别。首先是在小地震线性情况下识别出结构参数刚度和阻尼,然后在大地震下对隔震特性进行识别。算例表明,该方法对已知地震激励下的隔震结构,其非线性特性的识别具有较高的精度。这样可通过结构迟滞力的变化,对结构的隔震性能进行有效的识别。-Recently, as severe earthquake occurred one after another in different countries and caused huge losses of human life and properties, high buildings isolation and resistance have received great attention. Therefore, studies on buildings isolation performance in actual structure are significant. In this paper, an approach based on the extended Kalman estimator and least-squares estimation of unknown excitation is proposed to identify the nonlinear property of isolation layer without theoretical model. Firstly, structure parameters such as stiffness and damping are identified under minor earthquake. Then, nonlinear properties of isolation layer are identified under severe earthquake. The simulation results demonstrate that the proposed approach is capable of identifying the nonlinear property with good accuracy. So the isolation performance can be effectively recognized through the changing of the hysteresis force.
Platform: | Size: 4521984 | Author: hhh | Hits:

[OtherIMM1

Description: 基于卡尔曼滤波器的交互多模估计器,含有两个模型,跟踪误差计算完成-Interactive multi-mode estimator based on the Kalman filter contains two model tracking error calculation is complete
Platform: | Size: 2048 | Author: 赵梦 | Hits:

[Software EngineeringKalmanfilterofatwotanksystem.m

Description: to simulate the water level in the tanks. to verify its stability, controllability and observability. design kalman filter and define and simulate the Kalman estimator-Kalman filter of a two tank system
Platform: | Size: 2048 | Author: Lu | Hits:

[Windows DevelopKalman-Estimator_Code

Description: Kalman Estimation 1. Setup file: setup parameters 2. simulink file performs the estimator
Platform: | Size: 16384 | Author: nguyen | Hits:

[matlabmss_mmse_spzc

Description: In statistics and signal processing, a minimum mean square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE) of the fitted values of a dependent variable, which is a common measure of estimator quality. In the Bayesian setting, the term MMSE more specifically refers to estimation in a Bayesian setting with quadratic cost function. In such case, the MMSE estimator is given by the posterior mean of the parameter to be estimated. Since the posterior mean is cumbersome to calculate, the form of the MMSE estimator is usually constrained to be within a certain class of functions. Linear MMSE estimators are a popular choice since they are easy to use, calculate, and very versatile. It has given rise to many popular estimators such as the Wiener-Kolmogorov filter and Kalman filter
Platform: | Size: 1024 | Author: nagendra | Hits:

[matlabLMMSE

Description: In statistics and signal processing, a minimum mean square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE) of the fitted values of a dependent variable, which is a common measure of estimator quality. In the Bayesian setting, the term MMSE more specifically refers to estimation in a Bayesian setting with quadratic cost function. In such case, the MMSE estimator is given by the posterior mean of the parameter to be estimated. Since the posterior mean is cumbersome to calculate, the form of the MMSE estimator is usually constrained to be within a certain class of functions. Linear MMSE estimators are a popular choice since they are easy to use, calculate, and very versatile. It has given rise to many popular estimators such as the Wiener-Kolmogorov filter and Kalman filter.
Platform: | Size: 1024 | Author: Said | Hits:

[transportation applicationsestimator

Description: 通过卡尔曼滤波等方法,运用传感器信息对位置,姿态进行预测,从而能够得到系统的姿态和位置信息-Through the methods of kalman filter, using the sensor information to position, attitude to forecast, so that they can get posture and position information of the system
Platform: | Size: 131072 | Author: 邓丽敏 | Hits:

[AI-NN-PR卡尔曼滤波MATLAB仿真

Description: 在MATLAB仿真软件中实现卡尔曼滤波器,包含一些示例与案例,可供需要卡尔曼滤波的下载(  The Kalman Filter is an estimator for what is called the linear-quadratic problem, which is the problem of estimating the instantaneous "state".)
Platform: | Size: 36864 | Author: hanzb | Hits:

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