14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper WeA2.6

Tanaka, Hideyuki (Kyoto Univ.), Katayama, Tohru (Doshisha Univ.)

Identification of Dynamic Errors-In-Variables Models from Discrete Time Frequency Domain Power Spectra

Scheduled for presentation during the Regular Session "Errors in Variables Identification" (WeA2), Wednesday, March 29, 2006, 12:10−12:30, Banquet Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 17, 2018

Keywords Errors in Variables Identification


This paper considers a problem of identifying errors-in-variables (EIV) models under the assumption that a discrete frequency power spectrum is given. A new formulation of identifying dynamic EIV models is presented based on the prediction error approach, where the upper bound of the noise spectrum is taken into account by frequency weighting. An identification algorithm for EIV models is given via a subspace identification method and a J-spectral factorization technique. Based on the derived algorithm, uncertainty modeling is briefly discussed. Numerical simulation results are also included.