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ReBEL_0-2-6
- ReBEL is a Matlabtoolkit of functions and scr ipts, 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
equality_constraints_of_uncertain_systems_filterin
- 研究了一类离散不确定系统中存在等式约束时的最优滤波问题，在均方误差最小的意义下利用卡尔曼滤波给出了最优解。与传统的不确定滤波结果相比，从理论证明了利用更多信息的约束滤波的估计误差协方差的迹更小。-A class of discrete uncertain systems exist in the optimal filter when the equality constraint problem, the minimum mean square error in the sense of Ka
kalman-filter
- 当输入由白噪声产生的随机信号时，使期望输出和实际输出之间的均方根误差达到最小的线性系统。一种以状态变量的线性最小方差递推估算的方法。-When the input generated by the random white noise signal, the desired output and actual output of the RMS error to a minimum between the linear system. A kind of state variables of t
4floorearthquake
- 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。-Recentl
Adaptive-Online-Learning
- 基于EKF的神经网络自适应在线学习算法，包含例子和文档。-We show that a hierarchical Bayesian modeling approach allows us to perform regularization in sequential learning. We identify three inference levels within this hierarchy: model selection, parameter estimation, and
Kalman_matlab
- 卡尔曼滤波方法用于估计物体运动参数，卡尔曼滤波在运动目标跟踪问题中。超级推荐，绝对可以运行，随机模拟运动估计，效果非常不错，是个老外写的。-Kalman filtering method used to estimate the object motion parameters, the Kalman filter in moving object tracking problem. Super recommended, can definitely run, the stochastic si
NN_EKF
- 基于非线性扩展卡尔曼滤波的Matlab程序-The extended Kalman filter can not only estimate states of nonlinear dynamic systems from noisy measurements but also can be used to estimate parameters of a nonlinear system. A direct application of parameter estimation is to t
NN_UKF
- 基于无迹卡尔曼滤波的人工神经网络matlab程序-Similar to using the extended Kalman filter, Neural Networks can also be trained through parameter estimation using the unscented Kalman filter. This file provides a function for this purpose. It also includes an exampl
UKF
- 基于非线性动力系统的无迹卡尔曼滤波matlab程序-onlinear state estimation is a challenge problem. The well-known Kalman Filter is only suitable for linear systems. The Extended Kalman Filter (EKF) has become a standarded formulation for nonlinear state estimation.
uwb_TOA_positioning
- 该程序可以实现基于TOA估计的异步UWB定位。其中包括卡尔曼滤波、LSE估计、采用高斯函数作为冲激脉冲等-The program can achieve asynchronous UWB TOA estimation based positioning. Including Kalman filtering, LSE estimation using Gaussian function as impulse, etc.