Abstract
A time varying multivariate auto-regressive modeling of nonstationary time series is shown. An orthogonal polynomial Householder transformation least squares regression analysis modeling and the use of Akaike's AIC for subset selection are the key ideas in this method. Frequency domain relative power contribution computations yield an interpretation of the changing with time relationships in the analysis of single trial evoked potential electroencephalogram data.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
