In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kalman. Its purpose is to use measurements that are observed over time that contain noise (random variations) and other inaccuracies, and produce values that tend to be closer to the true values of the measurements and their associated calculated values. The Kalman filter has many applications in technology, and is an essential part of the development of space and military technology. Perhaps the most commonly used type of very simple Kalman filter is the phase-locked loop, which is now ubiquitous in FM radios and most electronic communications equipment. Extensions and generalizations to the method have also been developed.

matlab － Kalman
................\AR_to_SS.m
................\convert_to_lagged_form.m
................\ensure_AR.m
................\eval_AR_perf.m
................\kalman_filter.m
................\kalman_forward_backward.m
................\kalman_smoother.m
................\kalman_update.m
................\learning_demo.m
................\learn_AR.m
................\learn_AR_diagonal.m
................\learn_kalman.m
................\README.txt
................\README.txt~
................\sample_lds.m
................\smooth_update.m
................\SS_to_AR.m
................\tracking_demo.m

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