In this paper an approximate expression for the first inverse moment sf(1 - lambda) Sigma(k=1)(t) lambda(t-k)phi(k)phi(k)(T) + lambda(t) (1 - lambda)P-0(i-1), where phi(k) is a Gaussian stationary vector process is derived. This generalized quadratic form is the estimate of the information matrix when using the Recursive Least Squares (RLS) algorithm with forgetting factor. This estimator is commonly used when estimating parameters in time-varying linear stochastic systems. (C) 1998 Elsevier Science B.V. All rights reserved.
Subject classification (UKÄ)
- Probability Theory and Statistics