抄録
The determination of model order is an important problem in system identification. It is often determined by statistical test and information criteria. Recently a test method based on Lower-Diagonal-Upper triangular(LDU) decomposition was proposed in [1]. In this method the covariance matrix of input-output data is decomposed by LDU decomposition. It is well known that the rank of a covariance matrix equals the number of nonzero elements in the diagonal pivot matrix in the decomposition, and also equals model order. Thus the rank test in [1] is based on the asymptotic distributions of the pivots. But in some cases, the rank test can not provide the correct order of the model. Our purpose is to improve the accuracy of determination of model order using Minimum AIC Estimate(MAICE) and LDU decomposition.
