Model-Order Selection: A review of information criterion rules
2004 (English)In: IEEE Signal Processing Magazine, Vol. 21, no 4, 36-47 p.Article in journal (Refereed) Published
The parametric (or model-based) methods of signal processing require often not only the estimation of a vector of real-valued parameters but also the selection of one or several integer-valued parameters that are equally important for the specification of a data model. Examples of these integer-valued parameters of the model include the orders of an autoregressive moving average model, the number of sinusoidal components in a sinusoids-in-noise signal, and the number of source signals impinging on a sensor array. In each of these cases, the integer-valued parameters determine the dimension of the parameter vector of the data model, and they must be estimated from the data.
Place, publisher, year, edition, pages
2004. Vol. 21, no 4, 36-47 p.
AIC, BIC, GIC, ML
IdentifiersURN: urn:nbn:se:uu:diva-70180OAI: oai:DiVA.org:uu-70180DiVA: diva2:98091