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[Mathimatics-Numerical algorithms] EKF2 DL : 0: 通过MATLAB实现卡尔曼滤波并应用于初始对准，与航天人共享-Kalman filter to achieve the adoption of MATLAB and applied to initial alignment with the space to share
Date : 2025-07-01 Size : 1kb User : 刘俭飞
[matlab] EKF2 DL : 1: 原代码包括捷联惯导初始对准程序,实用性强,便于学习-chushiduizhun
Date : 2025-07-01 Size : 1kb User : liuhongen
[matlab] EKF2 DL : 0: 这是一个关于扩展卡尔曼滤波的源程序，可以帮助初学者学习该滤波算法-This is an extended Kalman filter on the source, can help beginners learn the filtering algorithm
Date : 2025-07-01 Size : 1kb User : daijie
[Other] EKF2 DL : 0: 永磁同步电机卡尔曼无速度传感器仿真在实践中的 -matlab for pmsm ekf
Date : 2025-07-01 Size : 1kb User : 戴玮
[Special Effects] ekfslam_v2.0 DL : 0: EKF2.0 利用扩展卡尔曼滤波器实现的SLAM算法，Matlab版本，是一个模拟的程序。运行方法为先载入mat，再运行XXX_sim函数。-EKF2.0 using the extended Kalman filter SLAM algorithm, Matlab version, is a simulation program. The method of operation for the first load the mat, run XXX_sim function.
Date : 2025-07-01 Size : 33kb User : 吴立彬
[AI-NN-PR] ekf2 DL : 0: 一种快速Kalman滤波算法实现,。对于某些不能够采取离线计算的滤波过程来说，它可以在保证一定精度的同时极大地提高计算速度和减少计算占用资源- EKF Extended Kalman Filter for nonlinear dynamic systems [x, P] = ekf(f,x,P,h,z,Q,R) returns state estimate, x and state covariance, P for nonlinear dynamic system: x_k+1 = f(x_k)+ w_k z_k = h(x_k)+ v_k where w ~ N(0,Q) meaning w is gaussian noise with covariance Q v ~ N(0,R) meaning v is gaussian noise with covariance R Inputs: f: function handle for f(x) x: a priori state estimate P: a priori estimated state covariance h: fanction handle for h(x) z: current measurement Q: process noise covariance R: measurement noise covariance Output: x: a posteriori state estimate P: a posteriori state covariance Example:
Date : 2025-07-01 Size : 3kb User : 柳兵