This paper presents a cost-effective adaptive feedback Active Noise Control (FANC) method for controlling functional Magnetic Resonance Imaging (fMRI) acoustic noise by decomposing it into dominant periodic components and residual random components. Periodicity of fMRI acoustic noise is exploited by using linear prediction (LP) filtering to achieve signal decomposition. A hybrid combination of adaptive filters-Recursive Least Squares (RLS) and Normalized Least Mean Squares (NLMS) are then used to effectively control each component separately. Performance of the proposed FANC system is analyzed and Noise attenuation levels (NAL) up to 32.27 dB obtained by simulation are presented which confirm the effectiveness of the proposed FANC method.

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.

No abstract