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| 8.
Direct Brain–Computer Communication |
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8.3.
Components of graz BCI
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8.3.1.
Parameter Estimation and Classification |
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8.3.1.2.
Adaptive Autoregressive Model |
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A classical approach for estimating time-varying
AR parameter is the segmentation based approach.
In this case, the data is divided into short segments and the
AR parameters are estimated from each segment. The result is
a time course of the AR parameters that describes the time-varying
characteristics of the process.
The segment length determines
the accuracy of the estimated parameters and defines the resolution
in time. The shorter the segment length, the higher is the time
resolution but this has the disadvantage of an increasing error
of the AR estimates.
Alternatively, the adaptive autoregressive(AAR) algorithms can perform calculation concurrent
to the data acquisition, where no buffering is required.
Source:
Motor Imagery and Direct Brain–Computer Communication, Gert Pfurtscheller and Christa Neuper 
