Regularization of the DREM Procedure for Parameter Estimation Under Partial Excitation
Abstract
This paper investigates the problem of estimation of unknown constant parameters in linear regression with measurement noise. Two concepts to analyze different types of excitation of the regressor are introduced: partial and feeble. The former indicates the absence of persistent or interval excitation, while the latter characterizes the presence of excitation that is inadequate for efficient estimation in a noisy environment. Furthermore, the paper proposes regularization techniques to improve the estimation performance of the dynamic regressor extension and mixing (DREM) method. The efficacy of theoretical findings is illustrated in the simulations.
Fields of Study & Subjects
Non-Destructive Testing Techniques
Magnetic Properties and Applications
Geophysical and Geoelectrical Methods
Publication details
- Journal / source
- IEEE Transactions on Automatic Control
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 71
- Issue
- 9
- Pages
- 6227–6234
- Publication date
- 13 April 2026
- Language
- EN