Real-time active noise control of multi-tones and MRI acoustic noise in fMRI bore with signal decomposition and parallel hybrid RLS-NLMS adaptive algorithms

This paper presents a real-time implementation of a cost-effective adaptive feedback Active Noise Control (FANC) method for attenuating acoustic multi-tone noise and functional Magnetic Resonance Imaging (fMRI) acoustic noise in a fMRI bore test-bed. Periodic property of the signal is used to decompose it into dominant periodic components and residual random components using linear prediction (LP) filtering. After decomposition, a hybrid combination of Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) filters is used to effectively attenuate each of the periodic and random components of noise separately. Real time implementation of proposed FANC method on fMRI test bed is discussed and Noise attenuation levels (NAL) obtained are presented which support the effectiveness of the FANC method in practice.