System identification from noisy measurements of inputs and outputs

DOI10.1016/0167-6911(83)90043-9zbMath0504.93068OpenAlexW2043285444MaRDI QIDQ1835898

Rikus Eising, Nico Linssen, Henk Rietbergen

Publication date: 1983

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-6911(83)90043-9

zbMATH Keywords

consistent estimatesmaximum likelihood estimatesnoisy measurementsasymptotic statistical propertiessensitivity of estimates

Mathematics Subject Classification ID

Related Items (1)

Errors-in-variables methods in system identification

Cites Work

• Unnamed Item
• New inversion formulas for matrices classified in terms of their distance from Toeplitz matrices
• Identification of stochastic linear systems in presence of input noise
• Approximate inference in multivariate nonlinear functional relationships
• Identification of noisy systems
• An efficient method for finding the minimum of a function of several variables without calculating derivatives
• On system identification from noise-obscured input and output measurements†

This page was built for publication: System identification from noisy measurements of inputs and outputs