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access icon openaccess Detection of weak monocycle sinusoidal signals with a low constant false alarm rate based on the support vector machine

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References

    1. 1)
      • 1. Darrer, B.J., Watson, J.C., Bartlett, P., et al: ‘Toward an automated setup for magnetic induction tomography’, Magn. IEEE Trans. Magn., 2015, 51, (1), pp. 14.
    2. 2)
      • 2. Liu, J.M., Yang, X., Gao, Y.L., et al: ‘Application of similar Liu system in underwater weak signal detection’, Acta Phys. Sin., 2016, 65, (7), pp. 4050.
    3. 3)
      • 3. Guo, J., Cai, X., Hu, T., et al: ‘Key technologies of tracking and positioning of intelligent robots in oil and gas pipelines: a review of recent advances’, Yi Qi Yi Biao Xue Bao/Chin. J. Sci. Instrum., 2015, 36, (3), pp. 481498.
    4. 4)
      • 4. Cai, X., Guo, J., Hu, T., et al: ‘Reverse optimization design of ELF magnetic transmitter for ferromagnetic pipeline’, Chin. J. Sci. Instrum., 2014, 35, (3), pp. 634641.
    5. 5)
      • 5. Chen, S., Guo, J., Hu, T.: ‘Distribution and detection of ELF weak magnetic field in ferromagnetic pipeline environment’, Chin. J. Sci. Instrum., 2011, 32, (10), pp. 23482356.
    6. 6)
      • 6. Guo, J., Bo, T., Xiong, C.: ‘Estimation and detection of the weak transient ELF signal based on the phase inverting double-peak exponential model’, Chin. J. Sci. Instrum., 2015, 36, (8), pp. 16821691.
    7. 7)
      • 7. Wang, C., Guo, J., Liu, H., et al: ‘Novel approach of real-time ELF weak signal detection based on least square algorithm’, Chin. J. Sci. Instrum., 2009, 30, (12), pp. 24682473.
    8. 8)
      • 8. Zheng, L., Geng, H., Yang, G.: ‘Fast and robust phase estimation algorithm for heavily distorted grid conditions’, IEEE Trans. Ind. Electron., 2016, 63, (11), pp. 68456855.
    9. 9)
      • 9. Wiebe, N., Granade, C.: ‘Efficient Bayesian phase estimation’, Phys. Rev. Lett., 2016, 117, (1), p. 010503.
    10. 10)
      • 10. Li, H., Wang, R., Cao, S., et al: ‘Weak signal detection using multiscale morphology in micro seismic monitoring’, J. Appl. Geophys., 2016, 133, pp. 3949.
    11. 11)
      • 11. Leng, Y. G., Wang, T.Y.: ‘Numerical research of twice sampling stochastic resonance for the detection of a weak signal submerged in a heavy noise’, Acta Phys. Sin., 2003, 52, (10), pp. 24322437.
    12. 12)
      • 12. Xiang, X., Shi, B.: ‘Weak signal detection based on the information fusion and chaotic oscillator’, Chaos, 2010, 20, (1), p. 013104.
    13. 13)
      • 13. Eski, İ., Temürlenk, A.: ‘Design of neural network-based control systems for active steering system’, Nonlinear Dyn., 2013, 73, (3), pp. 14431454.
    14. 14)
      • 14. Ivancevic, T., Jain, L., Pattison, J., et al: ‘Nonlinear dynamics and chaos methods in neurodynamics and complex data analysis’, Nonlinear Dyn., 2009, 56, (1), pp. 2344.
    15. 15)
      • 15. Hu, J., Zhang, Y., Yang, M., et al: ‘Weak transient signal detection method from strong chaotic interference based on convex optimization’, Nonlinear Dyn., 2016, 84, (3), pp. 19.
    16. 16)
      • 16. Cortes, C., Vapnik, V.: 'Support-vector Networks', Mach. Learn., 1995, 20, (3), pp. 273297.
    17. 17)
      • 17. Kosaka, N., Ohashi, G.: ‘Vision-based nighttime vehicle detection using censure and SVM’, IEEE Trans. Intell. Transp. Syst., 2015, 16, (5), pp. 110.
    18. 18)
      • 18. Murugavel, A.S., Ramakrishnan, S.: ‘Hierarchical multi-class SVM with ELM kernel for epileptic EEG signal classification’, Med. Biol. Eng. Comput., 2016, 54, (1), pp. 149161.
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