This is a feasibility study to develop system identification of noise cancellation algorithms for improving the signal-to-noise ratio of magnetoencephalographic (MEG) in nonshielded environments. The algorithms will be evaluated for offline noise cancellation given some samples of MEG data. These methods will primarily be evaluated for removal of random low frequency noise but will also be evaluated for the phase-locked removal of monochromatic machinery noise and line frequency noise from the sample data.
