Gaussian approximation in recursive estimation of multiple states of nonlinear Wiener systems
type: Item
instance of: scholarly article
title: Gaussian approximation in recursive estimation of multiple states of nonlinear Wiener systems
zbMATH Open document ID: 0638.93070
DOI: 10.1016/0005-1098(88)90033-7
author: O. L. R. Jacobs
published in: Automatica
publication date: 1988-01-01T00:00:00Z
review text: The paper concerns recursive state estimation in Wiener systems where the output is a scalar weighted sum of multiple states. A Gaussian approximation to the computed conditional probability distribution for the scalar sum of states is shown to lead to a practicable numerical algorithm for estimating the multiple states. This algorithm mimics the Kalman filter. Simulations show the method giving good performance when the nonlinearity is severe quantization.
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 62A01
Mathematics Subject Classification ID: 93C10
Mathematics Subject Classification ID: 93E11
Mathematics Subject Classification ID: 93E25
zbMATH DE Number: 4041762
zbMATH Keywords: quantization
zbMATH Keywords: recursive state estimation
zbMATH Keywords: Wiener systems
zbMATH Keywords: Gaussian approximation
zbMATH Keywords: algorithm
MaRDI profile type: Publication
full work available at URL: 0005-1098(88)90033-7
OpenAlex ID: W2029769730
cites work: Modelling estimation and control in the relief of post-operative pain
cites work: On controlling pH
cites work: Stochastic processes and filtering theory
description: scientific article; zbMATH DE number 4041762