Approaches to adaptive filtering
Approaches to adaptive filtering
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DOI：
10.1109/sap.1970.269992
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发表时间：
1970-12
期刊：
影响因子：
--
通讯作者：
R. Mehra
中科院分区：
文献类型：
--
作者：
R. Mehra
本文讨论了自适应滤波的几种方法。不同的方法分为四类：（i）贝叶斯方法，（ii）最大似然方法，（iii）相关方法，和（iv）协方差匹配方法。描述了方法之间的关系和与每种方法相关的困难。本文给出了直接估计卡尔曼滤波器最优增益的新算法。
In this expository paper, several approaches to Adaptive Filtering are discussed. The different methods are divided into four categories of (i) Bayesian Methods, (ii) Maximum Likelihood Methods, (iii) Correlation Methods, and (iv) Covariance-Matching Methods. The relationship between the methods and the difficulties associated with each method are described. New algorithms for the direct estimation of the optimal gain of a Kalman filter are given.