Weight Stacking Analysis of Delayless Subband Adaptive Algorithms for fMRI Active Noise Cancellation

High level acoustic noise in fMRI scanners is a source of concern to patients and health care providers. Active noise control systems employing delayless subband adaptive filters have been shown effective in fMRI acoustic noise reduction [3] [4]. In this method [5], adaptive filtering is done in subbands and the subband weights are stacked together to construct the fullband filter weights. There are two types of stacking methods called FFT and FFT-2. These stacking methods introduce distortion which limit the noise reduction level. In this paper, we model the distortion and analyze the effect of distortion when different adaptive schemes (nLMS, APA, RLS) are used. This analysis helps in selecting the appropriate adaptive scheme and determining the optimum number of subbands.