Sensorimotor rhythm-based brain–computer interface (BCI): model order selection for autoregressive spectral analysis
نویسندگان
چکیده
منابع مشابه
Sensorimotor rhythm-based brain-computer interface (BCI): model order selection for autoregressive spectral analysis.
People can learn to control EEG features consisting of sensorimotor rhythm amplitudes and can use this control to move a cursor in one or two dimensions to a target on a screen. Cursor movement depends on the estimate of the amplitudes of sensorimotor rhythms. Autoregressive models are often used to provide these estimates. The order of the autoregressive model has varied widely among studies. ...
متن کاملModel selection for integrated autoregressive processes of infinite order
Choosing good predictive models is an important ingredient in a great deal of statistical research. When the true model is relatively simple and can be parameterized by a prescribed finite set of parameters whose values are unknown, it is natural to ask whether a model selection criterion can exclude all redundant parameters, thereby achieving prediction efficiency through the most parsimonious...
متن کاملOrder selection for vector autoregressive models
Order-selection criteria for vector autoregressive (AR) modeling are discussed. The performance of an order-selection criterion is optimal if the model of the selected order is the most accurate model in the considered set of estimated models: here vector AR models. Suboptimal performance can be a result of underfit or overfit. The Akaike information criterion (AIC) is an asymptotically unbiase...
متن کاملOrder selection of autoregressive models
This correspondence addreskes the problem of order determination of autoregressive models by Bayesian predictive densities. A criterion is derived employing noninformative prior densities of the model parameters. The form of the obtained criterion coincides with that of Rissanen in 1161. Simulation results are presented which demonstrate the good performance of the criterion, and comparisons wi...
متن کاملFinite sample criteria for autoregressive order selection
The quality of selected AR models depends on the true process in the finite sample practice, on the number of observations, on the estimation algorithm, and on the order selection criterion. Samples are considered to be finite if the maximum candidate model order for selection is greater than 10, where denotes the number of observations. Finite sample formulae give empirical approximations for ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Neural Engineering
سال: 2008
ISSN: 1741-2560,1741-2552
DOI: 10.1088/1741-2560/5/2/006