Abstract
The optimal input design problem has been discussed for efficient order determination of autoregressive models under the input power constraint. By solving a mathematical programming problem, auto-caovariance sequence of an optimal input is derived, which maximizes the time-average of the Kullback divergence to make difference of the models bigger without making much effect on the original system behavior. The proposed approach is based on the sequential comparison of the AIC, and it can be applied to find the model structure of general linear time-invariant discrete-time systems.
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