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

Lookup NU author(s): Professor Jonathon Chambers


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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.

Publication metadata

Author(s): Shah SM, Samar R, Raja MAZ, Chambers JA

Publication type: Article

Publication status: Published

Journal: IET Electronics Letters

Year: 2014

Volume: 50

Issue: 14

Pages: 973-975

Print publication date: 03/07/2014

ISSN (print): 0013-5194

Publisher: The Institution of Engineering and Technology


DOI: 10.1049/el.2014.1275


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