|Publisher version (open access)||543 KB||Adobe Acrobat PDF||View/Open
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/30033
- On parameter estimation using nonparametric noise models
Mahata , Kaushik;
- Fitting multidimensional parametric models in frequency domain using nonparametric noise models is considered in this paper. A nonparametric estimate of the noise statistics is obtained from a finite number of independent data sets. The estimated noise model is then substituted for the the true noise covariance matrix in the maximum likelihood loss function to obtain suboptimal parameter estimates. The goal here is to present an analysis of the resulting estimates. Sufficient conditions for consistency are derived, and an asymptotic accuracy analysis is carried out. The first- and second-order statistics of the cost function at the global minimum point are also explored, which can be used for model validation. The analytical findings are validated using numerical simulation results.
- IEEE Transactions on Automatic Control Vol. 51, Issue 10, p. 1602-1612
- Publisher Link
- Institute of Electrical and Electronics Engineers (IEEE)
multiple-output (MIMO) systems;
nonparametric noise models;
- Resource Type
- journal article
- Copyright © 2006 IEEE. Reprinted from IEEE Transactions on Automatic Control, 51, 10, 1602-1612. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to email@example.com. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
- Full Text