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Is Kalman filter an algorithm?
Kalman filtering is an algorithm that provides estimates of some unknown variables given the measurements observed over time. Kalman filters have been demonstrating its usefulness in various applications. Kalman filters have relatively simple form and require small computational power.
How does EM algorithm work?
The EM algorithm can be used to estimate latent variables, like ones that come from mixture distributions (you know they came from a mixture, but not which specific distribution). It works by choosing random values for the missing data points, and using those guesses to estimate a second set of data.
What is Kalman filtering used for?
Kalman filters are used to optimally estimate the variables of interests when they can’t be measured directly, but an indirect measurement is available. They are also used to find the best estimate of states by combining measurements from various sensors in the presence of noise.
Which is an application of the Kalman filter?
A common application is for guidance, navigation, and control of vehicles, particularly aircraft, spacecraft and dynamically positioned ships. Furthermore, the Kalman filter is a widely applied concept in time series analysis used in fields such as signal processing and econometrics.
How are EM algorithms used in Computer Science?
EM algorithms and the Kalman filter are well-known and heavily used in engineering and computer science applications. For some general background on EM algorithms the reader is referred to McLachlan (1996) and to Harvey (1991) for EM algorithms for time series data. There are a multitude of books on the Kalman filter.
Related to the recursive Bayesian interpretation described above, the Kalman filter can be viewed as a generative model, i.e., a process for generating a stream of random observations z = (z 0, z 1, z 2.).
When was Kalman’s special case linear filter published?
In fact, some of the special case linear filter’s equations appeared in these papers by Stratonovich that were published before summer 1960, when Kalman met with Stratonovich during a conference in Moscow.