Output details
13 - Electrical and Electronic Engineering, Metallurgy and Materials
Queen's University Belfast
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Article title
Non-parametric nonlinear system identification: A data-driven orthogonal basis function approach
Type
D - Journal article
Title of journal
IEEE Transactions on Automatic Control
Article number
-
Volume number
53
Issue number
11
First page of article
2615
ISSN of journal
0018-9286
Year of publication
2008
URL
-
Number of additional authors
0
Additional information
The problem with identification using basis function is that sufficient a priori information on a unknown system must be available. This is not realistic in most applications. This paper presents a way to choose a basis function that is automatically determined by the data. In other words, basis choice and system identification are integrated parts of system identification. This eliminates the problem of blindly choosing a basis function and automatically finds the basis functions that match the system even though the system is unknown.
Interdisciplinary
-
Cross-referral requested
-
Research group
C - Energy, Power and Intelligent Control (EPIC)
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-