Journal Article

Fractional normalised filtered-error least mean squares algorithm for application in active noise control systems

Raja, M.A.Z., Shah, S.M., Samar, R., Chambers, J.A.

2014

Overview

A novel fractional normalised filtered-error least mean squares (FN-FeLMS) algorithm is designed for secondary path modelling in active noise control systems. The update is formed as a combination of the conventional LMS and a fractional update derived from the Riemann–Liouville differintegral operator. The algorithm is considered for (machine) noise reduction for a primary path with zero-mean binary or Gaussian sources as inputs. An anti-noise signal is generated to alleviate the effect of noise and to minimise the filtered error by improved secondary path modelling. The proposed arrangement is evaluated for a number of different scenarios by varying the step size and fractional orders. Simulation results show that the proposed technique is more robust to step size variation; it outperforms the traditional FeLMS approach in terms of convergence, model accuracy and steady-state performance for a given signal-to-noise ratio.

• Publisher: The Institution of Engineering and Technology,Institution of Engineering and Technology,John Wiley & Sons, Inc
• Subject: Acoustical engineering / Acoustics / Active noise control / active noise control system / Algorithmics. Computability. Computer arithmetics / Algorithms / antinoise signal / Applied sciences / Computer science; control theory; systems / Convergence / Exact sciences and technology / filtering theory / fractional normalised filtered‐error least mean squares algorithm / Fundamental areas of phenomenology (including applications) / Gaussian / Gaussian processes / Gaussian sources / Least mean squares algorithm / least mean squares methods / Modelling / Noise: its effects and control / Physics / Riemann–Liouville differintegral operator / secondary path modelling / Signal to noise ratio / Theoretical computing / zero‐mean binary sources