Methods of recursive identification deal with the problem of building mathematical models of signals and systems on-line, at the same time as data is being collected.Expand

This paper gives a tutorial overview of instrumental variable methods. Comparisons are made to the least-squares method. An analysis including consistency and asymptotic distribution of the parameter… Expand

From the Publisher:
The aim of this text is to give a comprehensive introduction to the field of stochastic dynamic systems, their estimation and control, including the provision of complete… Expand

We derive a simplified maximum-likelihood Gauss-Newton algorithm which provides asymptotically efficient estimates of these parameters of sinusoidal signals in noise.Expand

Abstract The least-squares method in system identification leads generally to biased parameter estimates. A conceptually simple modification is to estimate the bias and to compute compensated… Expand

Analysis of the large-sample second-order properties of multiple signal classification (MUSIC) and subspace rotation (SUR) methods, such as ESPRIT, for sinusoidal frequency estimation.Expand

Abstract The problem addressed in this note concerns the relationship between the minimizers of a given loss function parametrized in two different ways. The so-called “invariance principle” (IP)… Expand