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Shock and Vibration
Volume 2014, Article ID 848097, 7 pages
http://dx.doi.org/10.1155/2014/848097
Research Article

Denoising of Mechanical Vibration Signals Using Quantum-Inspired Adaptive Wavelet Shrinkage

17th Department, Ordnance Engineering College, Shijiazhuang, China
24th Department, Ordnance Engineering College, Shijiazhuang, China

Received 10 November 2013; Accepted 26 March 2014; Published 9 April 2014

Academic Editor: Valder Steffen Jr.

Copyright © 2014 Yan-long Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. C. Chesneau, J. Fadili, and J.-L. Starck, “Stein block thresholding for image denoising,” Applied and Computational Harmonic Analysis, vol. 28, no. 1, pp. 67–88, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. J. N. Taylor, D. E. Makarov, and C. F. Landes, “Denoising single-molecule FRET trajectories with wavelets and Bayesian inference,” Biophysical Journal, vol. 98, no. 1, pp. 164–173, 2010. View at Publisher · View at Google Scholar · View at Scopus
  3. A. Loza, D. Bull, N. Canagarajah, and A. Achim, “Non-Gaussian model-based fusion of noisy images in the wavelet domain,” Computer Vision and Image Understanding, vol. 114, no. 1, pp. 54–65, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. C. C. Liu, T. Y. Sun, S. J. Tsai, Y. Yu, and S. Hsieh, “Heuristic wavelet shrinkage for denoising,” Applied Soft Computing Journal, vol. 11, no. 1, pp. 256–264, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. C. M. Chou, “A threshold based wavelet denoising method for hydrological data modelling,” Water Resources Management, vol. 25, no. 7, pp. 1809–1830, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. G. Y. Chen and S. E. Qian, “Denoising of hyperspectral imagery using principal component analysis and wavelet shrinkage,” IEEE Transactions on Geoscience and Remote Sensing, vol. 49, no. 3, pp. 973–980, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. W. Y. Wang, H. Z. He, and Z. Y. Zi, “Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform,” Mechanical Systems and Signal Processing, vol. 24, no. 1, pp. 119–137, 2010. View at Publisher · View at Google Scholar · View at Scopus
  8. R. Shao, W. Hu, and J. Li, “Multi-fault feature extraction and diagnosis of gear transmission system using time-frequency analysis and wavelet threshold denoising based on EMD,” Shock and Vibration, vol. 20, no. 2, pp. 341–349, 2013. View at Google Scholar
  9. C. Cafaro and S. Mancini, “On Grover's search algorithm from a quantum information geometry viewpoint,” Physica A: Statistical Mechanics and its Applications, vol. 391, no. 4, pp. 1610–1625, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. J. Tsai, F. Hsiao, Y. Li, and J. Shen, “A quantum search algorithm for future spacecraft attitude determination,” Acta Astronautica, vol. 68, no. 7-8, pp. 1208–1218, 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. P. C. Li, K. P. Song, and F. H. Shang, “Double chains quantum genetic algorithm with application to neuro-fuzzy controller design,” Advances in Engineering Software, vol. 42, no. 10, pp. 875–886, 2011. View at Publisher · View at Google Scholar · View at Scopus
  12. Q. Niu, T. J. Zhou, M. R. Fei et al., “An efficient quantum immune algorithm to minimize mean flow time for hybrid flow shop problems,” Mathematics and Computers in Simulation, vol. 84, pp. 1–25, 2012. View at Publisher · View at Google Scholar
  13. R. Vasile, S. Olivares, M. A. Paris, and S. Maniscalco, “Continuous-variable quantum key distribution in non-Markovian channels,” Physical Review A-Atomic, Molecular, and Optical Physics, vol. 83, no. 4, Article ID 042321, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. A. Leverrier and P. Grangier, “Continuous-variable quantum-key-distribution protocols with a non-Gaussian modulation,” Physical Review A-Atomic, Molecular, and Optical Physics, vol. 83, no. 4, Article ID 042312, 2011. View at Publisher · View at Google Scholar · View at Scopus
  15. X. W. Fu, M. Y. Ding, and C. Cai, “Despeckling of medical ultrasound images based on quantum-inspired adaptivethreshold,” Electronics Letters, vol. 46, no. 13, pp. 21–22, 2010. View at Google Scholar
  16. Y. C. Eldar and A. V. Oppenheim, “Quantum signal processing,” IEEE Signal Processing Magazine, vol. 19, no. 6, pp. 12–32, 2002. View at Publisher · View at Google Scholar · View at Scopus
  17. D. L. Donoho and J. M. Johnstone, “Ideal spatial adaptation by wavelet shrinkage,” Biometrika, vol. 81, no. 3, pp. 425–455, 1994. View at Publisher · View at Google Scholar · View at Scopus
  18. U. D. Dwivedi and S. N. Singh, “Enhanced detection of power-quality events using intra and interscale dependencies of wavelet coefficients,” IEEE Transactions on Power Delivery, vol. 25, no. 1, pp. 358–366, 2010. View at Publisher · View at Google Scholar · View at Scopus