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ISTC-CC Abstract
Adaptive Filter with Frequency Tracking and Variable Learning Rate for Line Noise Removal
Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, September 2011.
John W. Kelly, Jennifer L. Collinger*, Alan D. Degenhart*, Daniel P. Siewiorek, Asim Smailagic, Wei Wang*
Carnegie Mellon University
*University of Pittsburgh
This paper presents a method for filtering line noise using an adaptive noise canceling (ANC) technique. This method effectively eliminates the sinusoidal contamination while achieving a narrower bandwidth than typical notch filters and without relying on the availability of a noise reference signal as ANC methods normally do. A sinusoidal reference is instead digitally generated and the filter efficiently tracks the power line frequency, which drifts around a known value. The filter's learning rate is also automatically adjusted to achieve faster and more accurate convergence and to control the filter's bandwidth. In this paper the focus of the discussion and the data will be electrocorticographic (ECoG) neural signals, but the presented technique is applicable to other recordings.
FULL PAPER: pdf
