Title :
Optimal selection of model order for a class of nonlinear systems using the bootstrap
Author :
Zoubir, Abdelhak M. ; Ralston, Jonathon C. ; Iskander, D. Robert
Author_Institution :
Signal Processing Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
Abstract :
Nonlinear system identification involves selecting the order of the given model based on the input-output data. A bootstrap model selection procedure which selects the model by minimising bootstrap estimates of the prediction error is developed. Bootstrap based model selection procedures are attractive because the bootstrap observations generated for the model selection can also be used in subsequent inference procedures. The proposed method is simple and computationally efficient
Keywords :
Volterra series; error analysis; identification; nonlinear systems; optimisation; prediction theory; probability; signal processing; Hammerstein series; Volterra series; bootstrap estimates; bootstrap model selection; bootstrap observations; computationally efficient method; inference procedures; input-output data; nonlinear system identification; optimal model order selection; prediction error; probabilities; signal processing; Australia; Costs; Kernel; Nonlinear systems; Parameter estimation; Predictive models; Signal processing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.604781
