The Akaike Information Criterion With Parameter Uncertainty
An instance crucial to most problems in signal processing is the selection of the order of a candidate model. Among the different exciting criteria, the two most popular model selection criteria in the signal processing literature have been the Akaike's criterion AIC and the Bayesian Information criterion BIC, These criteria are similar in form in that they consist of data and penalty terms. Different approaches have been used used to derive these criteria. However, none of them take into...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 4th IEEE Workshop on Sensor Array and Multichannel Processing|
|01_Seghouane_The_Akaike_Information_2006.pdf||111.81 kB||Adobe PDF||Request a copy|
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