Understanding the Kalman Filter
作者： Richard J. Meinhold , Nozer D. Singpurwalla
DOI: 10.1080/00031305.1983.10482723
关键词: Artificial intelligence 、 Extended Kalman filter 、 Machine learning 、 Computer science 、 Multivariate normal distribution 、 Kalman filter 、 Ensemble Kalman filter 、 Multivariate statistics 、 Bayesian inference 、 Exponential smoothing 、 Data mining 、 Simple (abstract algebra)
摘要: Abstract This is an expository article. Here we show how the successfully used Kalman filter, popular with control engineers and other scientists, can be easily understood by statisticians if use a Bayesian formulation some well-known results in multivariate statistics. We also give simple example illustrating of filter for quality work.
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