Hybrid FxRLS-FxNLMS Adaptive Algorithm for Active Noise Control in fMRI Application

• Published in: IEEE transactions on control systems technology Vol. 19; no. 2; pp. 474 - 480
• Main Authors: Reddy, R M, Panahi, I M S, Briggs, R
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.03.2011; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acoustic noise control; Acoustics; Active noise control; active noise control (ANC); Active noise reduction; Adaptive algorithm; Adaptive algorithms; adaptive filtering; Adaptive filters; adaptive signal processing; Algorithms; Applied sciences; Biological and medical sciences; biomedical application; Computation; Computer science; control theory; systems; Control systems; Control theory. Systems; Convergence; Errors; Exact sciences and technology; functional magnetic resonance imaging (fMRI); Fundamental areas of phenomenology (including applications); Hardware; Investigative techniques, diagnostic techniques (general aspects); Least squares method; Least squares methods; Medical sciences; Modelling and identification; Noise control; Noise: its effects and control; Physics; Radiodiagnosis. Nmr imagery. Nmr spectrometry; Real time systems; Stability; Steady-state; Studies; Infinite impulse response filter; Capability index; Adaptive algorithm; Adaptive filtering; functional magnetic resonance imaging (fMRI); Acoustics; Functional analysis; Real time; Computational complexity; Nuclear magnetic resonance imaging; Noise control; Adaptive method; Steady state; Acoustic noise control; adaptive signal processing; Least squares method; High speed; Signal processing; Medical imagery; biomedical application; Active noise control; Biomedical engineering; active noise control (ANC)
• ISSN: 1063-6536; 1558-0865
• DOI: 10.1109/TCST.2010.2042599

A hybrid adaptive algorithm is developed for an active noise control system that leverages the stability of the filtered-input normalized least mean squares (FxNLMS) adaptive algorithm, with the high convergence speed of the filtered-input recursive least squares (FxRLS) adaptive algorithm. This algorithm is motivated by practical issues in implementing a real-time active noise control system. It leads to fast initial convergence with low, stable steady-state error while being limited by the computational capability of hardware. It gives better convergence speed than either the FxNLMS or FxRLS algorithm individually, lower residual error, and a lower overall computational complexity than the FxRLS algorithm, when appropriate filter lengths are chosen. Experimental results are presented for the implementation of the hybrid algorithm to cancel functional magnetic resonance imaging (fMRI) acoustic noise in an fMRI test-bed.