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EnsembleKalman_filter
- 集合卡尔曼滤波(EnKF) 数据同化方法可以避免了EKF 中协方差演变方程预报过程中出现的计算不准确和关于协方差矩阵的大量数据的存储问题,最主要的是可以有效的控制估计误差方差的增长,改善预报的效果。-Ensemble Kalman Filter (EnKF) data assimilation methods can be avoided in the EKF covariance forecasting the evolution equation arising in the course
Kalman
- 卡尔曼滤波的实例集合，适用于各种预测、数值估计、拟合等问题的解决，有详细的代码辅助说明。-Kalman filter collection of instances for a variety of forecasting, numerical estimation, fitting problems, a detailed code help.
Scalarmodel
- Evesen开发的scalarmodel，耦合了集合卡尔曼滤波算法和集合卡尔曼平滑算法-Scalarmodel coupled with Ensembled Kalman Filter and Ensembled Kalman Smoother
ENPF
- 集合卡尔曼粒子滤波算法matlab代码，能处理非高斯、非线性、多维状态的情况-Ensemble Kalman partilce filter algorithm using matlab code, can handle non-Gaussian, nonlinear, multidimensional state
EnKF集合卡尔曼滤波代码
- EnKF集合卡尔曼滤波代码，用于读写模式集合，包括两种扰动观测分析方案。(These files illustrate the model used for storing, reading and writing the ensemble of model states.)