Wavelet Based OE Model Identification with Random Missing Data
نویسندگان
چکیده
Based on wavelet representation theory, this paper proposes a novel identification algorithm with random missing data under the condition that the identified dynamic process can be described as an output error (OE) model structure. This new algorithm mainly consists of two stages: one is the wavelet reconstruction, the other the prediction for missing data using the identified model. For the sake of its application, selection of the final iteration number and the adopted wavelet category is also considered. Finally, numerical simulations are given to verify the satisfactory effectiveness of the proposed algorithm.
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