A Novel Adaptive State Detector-Based Post-Filtering Active Control Algorithm for Gaussian Noise Environment with Impulsive Interference
Abstract
:Featured Application
Abstract
1. Introduction
2. Proposed Algorithms
2.1. Preliminary
2.2. PFxNLMS with M-Estimate Function
2.3. Novel Recursive State Detector
2.4. Statistical Analysis of the Proposed Recursive Detection Method
3. Simulations
3.1. Random Impulsive Interference
3.2. Periodic Impulsive Interference
3.3. Robustness Analysis
4. Experiments
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Kuo, S.M.; Morgan, D.R. Active Noise Control Systems: Algorithms and DSP Implementations; Wiley: New York, NY, USA, 1996. [Google Scholar]
- Zimmermann, M.; Dostert, K. Analysis and modelling of impulsive noise in broad-band powerline communications. IEEE Trans. Electromagn. Compat. 2002, 44, 249–258. [Google Scholar] [CrossRef]
- Lui, L.; Gujjula, S.; Thanigai, P.; Kuo, S.M. Still in Womb: Intrauterine acoustic embedded active noise control for infant incubators. Adv. Acoust. Vib. 2008, 10. [Google Scholar] [CrossRef]
- Georgiou, P.G.; Tsakalides, P.; Kyriakakis, C. Alpha-stable modeling of noise and robust time-delay estimation in the presence of impulsive noise. IEEE Trans. Multimed. 1999, 10, 291–301. [Google Scholar] [CrossRef]
- Leahy, R.; Zhou, Z.; Hsu, Y.C. Adaptive filtering of stable processes for active attenuation of impulsive noise. In Proceedings of the 1995 International Conference on Acoustics, Speech, and Signal Processing, Detroit, MI, USA, 9–12 May 1995; pp. 2983–2986. [Google Scholar]
- Sun, X.; Kuo, S.M.; Meng, G.A. Adaptive algorithm for active control of impulsive noise. J. Sound Vib. 2006, 291, 516–522. [Google Scholar] [CrossRef]
- Akhtar, M.T.; Mitsuhashi, W. Improving performance of FxLMS algorithm for active noise control of impulsive noise. J. Sound Vib. 2009, 327, 647–656. [Google Scholar] [CrossRef]
- Wu, L.F.; He, H.S.; Qiu, X. An active impulsive noise control algorithm with logarithmic transformation. IEEE Trans. Audio Speech Lang. 2011, 19, 1041–1044. [Google Scholar] [CrossRef]
- Li, P.; Yu, X. Active noise cancellation algorithms for impulsive noise. Mech. Syst. Signal Proc. 2013, 36, 630–635. [Google Scholar] [CrossRef] [PubMed]
- Tan, L.; Jiang, J. Active control of impulsive noise using a nonlinear companding function. Mech. Syst. Signal Proc. 2015, 58, 29–40. [Google Scholar] [CrossRef]
- Al-Sayed, S.; Zoubir, A.M.; Sayed, A.H. Robust adaptation in impulsive noise. IEEE Trans. Signal Process. 2016, 65, 2851–2865. [Google Scholar] [CrossRef]
- Akhtar, M.T.; Mitsuhashi, W. Improving robustness of filtered-x least mean p-power algorithm for active attenuation of standard symmetric-α-stable impulsive noise. Appl. Acoust. 2011, 72, 688–694. [Google Scholar] [CrossRef]
- Wu, L.F.; Qiu, X. Active impulsive noise control algorithm with post adaptive filter coefficient filtering. IET Signal Process. 2013, 7, 515–521. [Google Scholar] [CrossRef]
- Bergamasco, M.; Della Rossa, F.; Piroddi, L. Active noise control with on-line estimation of non-Gaussian noise characteristics. J. Sound Vib. 2012, 331, 27–40. [Google Scholar] [CrossRef]
- Lu, L.; Zhao, H. Active noise control using maximum correntropy with adaptive kernel size. Mech. Syst. Signal Proc. 2017, 87, 180–191. [Google Scholar] [CrossRef]
- Mahmood, A.; Chitre, M. Optimal and Near-Optimal Detection in Bursty Impulsive Noise. IEEE J. Ocean. Eng. 2017, 42, 639–653. [Google Scholar] [CrossRef]
- Otsu, N. A threshold selection method from gray-level histograms. IEEE Syst. Man Cyben. B 1979, 9, 62–66. [Google Scholar] [CrossRef]
- Nikias, C.L.; Shao, M. Signal Processing with Alpha-Stable Distributions and Applications; Wiley-Interscience: New York, NY, USA, 1995. [Google Scholar]
- Liu, W.; Pokharel, P.P.; Principe, J.C. Correntropy: Properties and applications in non-gaussian signal processing. IEEE Trans. Signal Process. 2007, 55, 5286–5298. [Google Scholar] [CrossRef]
- Zhou, Y.; Yin, Y.; Zhang, Q. An optimal repetitive control algorithm for periodic impulsive noise attenuation in a non-minimum phase ANC system. Appl. Acoust. 2013, 74, 1175–1181. [Google Scholar] [CrossRef]
- Sun, G.; Li, M.; Lim, T.C. A family of threshold based robust adaptive algorithms for active impulsive noise control. Appl. Acoust. 2015, 97, 30–36. [Google Scholar] [CrossRef]
- Mirza, A.; Zeb, A.; Sheikh, S.A. Robust adaptive algorithm for active control of impulsive noise. EURASIP J. Adv. Signal Process. 2016, 44. [Google Scholar] [CrossRef]
- Kurian, N.C.; Patel, K.; George, N.V. Robust active noise control: An information theoretic learning approach. Appl. Acoust. 2017, 117, 180–184. [Google Scholar] [CrossRef]
- Luo, L.; Sun, J. A novel bilinear functional link neural network filter for nonlinear active noise control. Appl. Soft. Comput. 2018, 68, 636–650. [Google Scholar] [CrossRef]
- He, J.; Lam, B.; Shi, D.; Gan, W.S. Exploiting the Underdetermined System in Multichannel Active Noise Control for Open Windows. Appl. Sci. 2019, 9, 390. [Google Scholar] [CrossRef]
Initialization and parameter selection |
Length of primary path , length of secondary path . |
Step size of proposed method: |
Length of weightvector M Initiate angle |
Length of sliding windows: , |
Length of quantity levels: L |
Brief operations |
While available do |
, , , compare with |
Updating |
Updating |
end While |
Algorithms | Additions/Subtractions | Multiplications | Divisions | Exponential Operations |
---|---|---|---|---|
FxLMS | No | No | ||
FxlogLMS | 1 | 1 | ||
PFxNLMS | 1 | No | ||
FxRMC | 5 | 1 | ||
DMPFxNLMS | 1 |
Algorithms | Parameters |
---|---|
FxLMS | |
FxlogLMS | |
PFxNLMS | |
FxRMC | |
DMPFxNLMS | , initial |
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Zhu, W.; Shi, S.; Luo, L.; Sun, J. A Novel Adaptive State Detector-Based Post-Filtering Active Control Algorithm for Gaussian Noise Environment with Impulsive Interference. Appl. Sci. 2019, 9, 1176. https://doi.org/10.3390/app9061176
Zhu W, Shi S, Luo L, Sun J. A Novel Adaptive State Detector-Based Post-Filtering Active Control Algorithm for Gaussian Noise Environment with Impulsive Interference. Applied Sciences. 2019; 9(6):1176. https://doi.org/10.3390/app9061176
Chicago/Turabian StyleZhu, Wenzhao, Shengguo Shi, Lei Luo, and Jinwei Sun. 2019. "A Novel Adaptive State Detector-Based Post-Filtering Active Control Algorithm for Gaussian Noise Environment with Impulsive Interference" Applied Sciences 9, no. 6: 1176. https://doi.org/10.3390/app9061176