Identification of System Behaviours by Approximation of Time Series Data
January 1997
Research Paper
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The behavioural framework has several attractions to offer for the identification of multivariable systems. Some of the variables may be left unexplained without the need for a distinction between inputs and outputs; criteria for model quality are independent of the chosen parametrization; and behaviours allow for a global (i.e., non-local) approximation of the system dynamics. This is illustrated with a behavioural least squares method with an application in dynamic factor analysis.
Keywords
Automatically Extracted Terms
- system
- model
- method
- factor
- process
- identi
- system identi cation
- cation
- behaviour
- error
- identi cation
- behavioural
- approximation
- matrix
- square
- frequency
- time series
- function
- factor models
- complexity
