Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise Control
Active Noise Control (ANC) is an effective technique for removing undesirable disturbances based on destructive interference between two noises (i.e., the superposition principle). To reduce the Non-Gaussian distribution of impulsive noises, the ANC is implemented using a prominent Filtered Cross Le...
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| Format: | Article |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10473045/ |
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| author | Suman Turpati Ajay Roy K. C. T. Swamy Mohammad Khalid Imam Rahmani Masood Ur Rehman Sudan Jha Sultan Ahmad Jabeen Nazeer Hikmat A. M. Abdeljaber Yasser Eid Aljohani |
| author_facet | Suman Turpati Ajay Roy K. C. T. Swamy Mohammad Khalid Imam Rahmani Masood Ur Rehman Sudan Jha Sultan Ahmad Jabeen Nazeer Hikmat A. M. Abdeljaber Yasser Eid Aljohani |
| author_sort | Suman Turpati |
| collection | DOAJ |
| description | Active Noise Control (ANC) is an effective technique for removing undesirable disturbances based on destructive interference between two noises (i.e., the superposition principle). To reduce the Non-Gaussian distribution of impulsive noises, the ANC is implemented using a prominent Filtered Cross Least Mean Square (FxLMS) method that relies on reducing the unwanted noise. The standard FxLMS method fails to adapt to its specifications, resulting in poor convergence and instability in the presence of impulsive noises and a non-linear response from the ANC system’s components. The Least Square family of Recursive Least Square (RLS) increases ANC performance by offering superior convergence performance to traditional stochastic algorithms. This paper proposes a novel technique called the recursive non-linear active threshold-based and modified gain FXRLS (NAMGFxRLS) algorithm to overcome the inadequacies of impulsive noise and non-linearity issues in the ANC. The suggested technique aims to automatically modify weights by the various sample processes, i.e., employing the FxRLS algorithm’s updated gain to adjust the error and reference signals and appropriately deploying the threshold. The potential of the suggested strategy is proved by simulated results of convergence speed, stability, and excellent Mean Noise Reduction of roughly 52.8 % for various noises when compared to previous approaches, notably large impulsive noises. |
| first_indexed | 2024-04-24T17:05:54Z |
| format | Article |
| id | doaj.art-3e9b240a42ff4badaaf3efd75567820f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-24T17:05:54Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-3e9b240a42ff4badaaf3efd75567820f2024-03-28T23:00:22ZengIEEEIEEE Access2169-35362024-01-0112432224323410.1109/ACCESS.2024.337806710473045Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise ControlSuman Turpati0https://orcid.org/0000-0002-0842-1315Ajay Roy1K. C. T. Swamy2Mohammad Khalid Imam Rahmani3https://orcid.org/0000-0002-1937-7145Masood Ur Rehman4Sudan Jha5https://orcid.org/0000-0002-1937-7145Sultan Ahmad6https://orcid.org/0000-0002-1937-7145Jabeen Nazeer7Hikmat A. M. Abdeljaber8Yasser Eid Aljohani9Department of Electronics and Communication Engineering, G. Pullaiah College of Engineering and Technology, Andhra Pradesh, Kurnool, IndiaDepartment of Electronics and Communication Engineering, Lovely Professional University, Punjab, Phagwara, IndiaDepartment of Electronics and Communication Engineering, G. Pullaiah College of Engineering and Technology, Andhra Pradesh, Kurnool, IndiaCollege of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi ArabiaCollege of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi ArabiaDepartment of Computer Science and Engineering, School of Engineering, Kathmandu University, Kathmandu, Banepa, NepalDepartment of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi ArabiaDepartment of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi ArabiaDepartment of Computer Science, Faculty of Information Technology, Applied Science Private University, Amman, JordanCollege of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi ArabiaActive Noise Control (ANC) is an effective technique for removing undesirable disturbances based on destructive interference between two noises (i.e., the superposition principle). To reduce the Non-Gaussian distribution of impulsive noises, the ANC is implemented using a prominent Filtered Cross Least Mean Square (FxLMS) method that relies on reducing the unwanted noise. The standard FxLMS method fails to adapt to its specifications, resulting in poor convergence and instability in the presence of impulsive noises and a non-linear response from the ANC system’s components. The Least Square family of Recursive Least Square (RLS) increases ANC performance by offering superior convergence performance to traditional stochastic algorithms. This paper proposes a novel technique called the recursive non-linear active threshold-based and modified gain FXRLS (NAMGFxRLS) algorithm to overcome the inadequacies of impulsive noise and non-linearity issues in the ANC. The suggested technique aims to automatically modify weights by the various sample processes, i.e., employing the FxRLS algorithm’s updated gain to adjust the error and reference signals and appropriately deploying the threshold. The potential of the suggested strategy is proved by simulated results of convergence speed, stability, and excellent Mean Noise Reduction of roughly 52.8 % for various noises when compared to previous approaches, notably large impulsive noises.https://ieeexplore.ieee.org/document/10473045/Active noise controlactive functionsFxLMSsymmetric α stable distributionsrecursive least square |
| spellingShingle | Suman Turpati Ajay Roy K. C. T. Swamy Mohammad Khalid Imam Rahmani Masood Ur Rehman Sudan Jha Sultan Ahmad Jabeen Nazeer Hikmat A. M. Abdeljaber Yasser Eid Aljohani Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise Control IEEE Access Active noise control active functions FxLMS symmetric α stable distributions recursive least square |
| title | Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise Control |
| title_full | Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise Control |
| title_fullStr | Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise Control |
| title_full_unstemmed | Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise Control |
| title_short | Robust Non-Linear Active Function-Based FxRLS for Impulsive Active Noise Control |
| title_sort | robust non linear active function based fxrls for impulsive active noise control |
| topic | Active noise control active functions FxLMS symmetric α stable distributions recursive least square |
| url | https://ieeexplore.ieee.org/document/10473045/ |
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