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Awesome GitHub RepositoriesFixed-Lag Smoothing Algorithms
Algorithms that refine historical state estimates by incorporating a window of future observations.
Distinct from Fixed-Size Window Calculations: Existing candidates are for UI window management or basic subarray calculations, not signal state refinement.
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- rlabbe/filterpy
rlabbe/filterpy
3,772Auf GitHub ansehenfilterpy is a toolkit for Bayesian state estimation, Gaussian statistical analysis, and time-series noise reduction. It provides a library of linear and non-linear Kalman filters, as well as routines for non-Gaussian state estimation and signal smoothing. The project implements a variety of estimation methods, including particle filtering using Markov Chain Monte Carlo and resampling, and discrete Bayes filtering. It also includes a suite of algorithms for refining historical state estimates through backward and fixed-lag smoothing. Additional capabilities cover multivariate Gaussian analysi
Implements fixed-lag smoothing to refine historical state estimates using a window of future data.
Python
