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A discussion of model accuracy in system identification
Author(s) -
Ljung Lennart
Publication year - 1992
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.4480060304
Subject(s) - identification (biology) , computer science , prime (order theory) , errors in variables models , system identification , random error , machine learning , algorithm , data mining , statistics , mathematics , botany , combinatorics , biology , measure (data warehouse)
Model quality and model accuracy are of prime interest in system identification. In this contribution we will review and discuss these concepts. In particular we will split model errors into contributions from a ‘random error’ and a ‘bias error’ and describe and discuss how to assess these two concepts.