Approaches to adaptive filtering

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.