A survey of the most frequently used criteria for determination of the order of autoregressive models is presented. Algorithms based on extremal filtration, linear forecasting, as well as addition of a reference component to the signal are proposed. It is demonstrated that neural networks may be used to solve the problem.
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Translated from Izmeritel’naya Tekhnika No. 4 pp. 38–41 2011.
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Dmitrienko, A.G., Myasnikova, M.G. & Tsypin, B.V. Estimating the order of autoregressive models in approximation of signals. Meas Tech 54, 416–421 (2011). https://doi.org/10.1007/s11018-011-9741-9
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DOI: https://doi.org/10.1007/s11018-011-9741-9