Sequential parameter estimation for dynamical systems in the presence of multiplicative and additive noises in the observations
type: Item
instance of: scholarly article
title: Sequential parameter estimation for dynamical systems in the presence of multiplicative and additive noises in the observations
zbMATH Open document ID: 0582.93060
published in: Automation and Remote Control
publication date: 1985-01-01T00:00:00Z
review text: The paper considers the estimation of the parameters in linear-in- parameters models which include two noise sources. The description of the first noise source is by means of its second-order properties but that of the second noise source is less standard. This second noise is assumed to be bounded by some known function of the measurements. A modified least- squares method for estimating the parameters in this type of models is proposed, and its properties are established. Next, it is shown that the problem of estimating the parameters of an autoregressive model with both additive and multiplicative noise can be reduced to the type of problem analysed previously. The estimates proposed are shown to be robust in the sense that they possess a prescribed accuracy which holds for a whole class of distribution functions of the measurements.
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 62L12
Mathematics Subject Classification ID: 93C05
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62F35
Mathematics Subject Classification ID: 93E12
zbMATH DE Number: 3932919
zbMATH Keywords: estimation
zbMATH Keywords: linear-in-parameters models
zbMATH Keywords: modified least-squares method
zbMATH Keywords: autoregressive model
zbMATH Keywords: additive and multiplicative noise
author: Vyacheslav A. Vasiliev
author: Victor Konev
reviewed by: Petre Stoica
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 3932919