Specific Emitter Identification Based on Refined Composite Multiscale Dispersion Entropy
 K. I. Talbot, P. R. Duley, and M. H. Hyatt, “Specific emitter identification
and verification,” Technology Review, vol. 113, 2003.
 Z. Li, Y. Yin, and L. Wu, “Radio frequency fingerprint identification
method in wireless communication,” in International Conference on
Machine Learning and Intelligent Communications. Springer, 2017,
 I. O. Kennedy, P. Scanlon, F. J. Mullany, M. M. Buddhikot, K. E. Nolan,
and T. W. Rondeau, “Radio transmitter fingerprinting: A steady state
frequency domain approach,” in 2008 IEEE 68th Vehicular Technology
Conference. IEEE, 2008, pp. 1–5.
 H. C. Choe, C. E. Poole, M. Y. Andrea, and H. H. Szu, “Novel
identification of intercepted signals from unknown radio transmitters,”
in Wavelet Applications II, vol. 2491. International Society for Optics
and Photonics, 1995, pp. 504–518.
 J. Toonstra and W. Kinsner, “Transient analysis and genetic algorithms
for classification,” in IEEE WESCANEX 95. Communications, Power,
and Computing. Conference Proceedings, vol. 2. IEEE, 1995, pp.
 R. Klein, M. A. Temple, M. J. Mendenhall, and D. R. Reising,
“Sensitivity analysis of burst detection and rf fingerprinting
classification performance,” in 2009 IEEE International Conference on
Communications. IEEE, 2009, pp. 1–5.
 W. C. Suski II, M. A. Temple, M. J. Mendenhall, and R. F. Mills, “Using
spectral fingerprints to improve wireless network security,” in IEEE
GLOBECOM 2008-2008 IEEE Global Telecommunications Conference.
IEEE, 2008, pp. 1–5.
 S. U. Rehman, K. Sowerby, and C. Coghill, “Rf fingerprint extraction
from the energy envelope of an instantaneous transient signal,” in 2012
Australian Communications Theory Workshop (AusCTW). IEEE, 2012,
 H. Yuan and A. Hu, “Preamble-based detection of wi-fi transmitter rf
fingerprints,” Electronics letters, vol. 46, no. 16, pp. 1165–1167, 2010.
 P. Padilla, J. Padilla, and J. Valenzuela-Valdes, “Radio frequency
identification of wireless devices based on rf fingerprinting,” Electronics
Letters, vol. 49, no. 22, pp. 1409–1410, 2013.
 A. Candore, O. Kocabas, and F. Koushanfar, “Robust stable radiometric
fingerprinting for wireless devices,” in 2009 IEEE International
Workshop on Hardware-Oriented Security and Trust. IEEE, 2009, pp.
 Y. Huang and H. Zheng, “Radio frequency fingerprinting based on
the constellation errors,” in 2012 18th Asia-Pacific Conference on
Communications (APCC). IEEE, 2012, pp. 900–905.
 V. Brik, S. Banerjee, M. Gruteser, and S. Oh, “Wireless device
identification with radiometric signatures,” in Proceedings of the 14th
ACM international conference on Mobile computing and networking.
ACM, 2008, pp. 116–127.
 R. W. Klein, M. A. Temple, and M. J. Mendenhall, “Application of
wavelet-based rf fingerprinting to enhance wireless network security,”
Journal of Communications and Networks, vol. 11, no. 6, pp. 544–555,
 C. Bertoncini, K. Rudd, B. Nousain, and M. Hinders, “Wavelet
fingerprinting of radio-frequency identification (rfid) tags,” IEEE
Transactions on Industrial Electronics, vol. 59, no. 12, pp. 4843–4850,
 L. Xuan-min, Y. Ju, and Z. Ya-jian, “A new method based on local
integral bispectra and svm for radio transmitter individual identification,”
in 2010 WASE international conference on information engineering,
vol. 4. IEEE, 2010, pp. 65–68.
 S. Xu, L. Xu, Z. Xu, and B. Huang, “Individual radio transmitter
identification based on spurious modulation characteristics of signal
envelop,” in MILCOM 2008-2008 IEEE Military Communications
Conference. IEEE, 2008, pp. 1–5.
 T. Carroll, “A nonlinear dynamics method for signal identification,”
Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 17, no. 2,
p. 023109, 2007.
 J. S. Richman and J. R. Moorman, “Physiological time-series analysis
using approximate entropy and sample entropy,” American Journal
of Physiology-Heart and Circulatory Physiology, vol. 278, no. 6, pp.
 M. Rostaghi and H. Azami, “Dispersion entropy: A measure for
time-series analysis,” IEEE Signal Processing Letters, vol. 23, no. 5,
pp. 610–614, 2016.
 Y. Xie, S. Wang, E. Zhang, and Z. Zhao, “Specific emitter identification
based on nonlinear complexity of signal,” in 2016 IEEE International
Conference on Signal Processing, Communications and Computing
(ICSPCC). IEEE, 2016, pp. 1–6.
 G. Baldini, R. Giuliani, G. Steri, and R. Neisse, “Physical layer
authentication of internet of things wireless devices through permutation
and dispersion entropy,” in 2017 Global Internet of Things Summit
(GIoTS). IEEE, 2017, pp. 1–6.
 S. Deng, Z. Huang, X. Wang, and G. Huang, “Radio frequency
fingerprint extraction based on multidimension permutation entropy,”
International Journal of Antennas and Propagation, vol. 2017, 2017.
 G. Huang, Y. Yuan, X. Wang, and Z. Huang, “Specific emitter
identification based on nonlinear dynamical characteristics,” Canadian
Journal of Electrical and Computer Engineering, vol. 39, no. 1, pp.
 H. Azami, E. Kinney-Lang, A. Ebied, A. Fern´andez, and J. Escudero,
“Multiscale dispersion entropy for the regional analysis of resting-state
magnetoencephalogram complexity in alzheimer’s disease,” in 2017 39th
Annual International Conference of the IEEE Engineering in Medicine
and Biology Society (EMBC). IEEE, 2017, pp. 3182–3185.
 H. Azami, M. Rostaghi, D. Ab´asolo, and J. Escudero, “Refined
composite multiscale dispersion entropy and its application to
biomedical signals,” IEEE Transactions on Biomedical Engineering,
vol. 64, no. 12, pp. 2872–2879, 2017.
 M. Costa, A. L. Goldberger, and C.-K. Peng, “Multiscale entropy
analysis of biological signals,” Physical review E, vol. 71, no. 2, p.
 C. Bandt and B. Pompe, “Permutation entropy: a natural complexity
measure for time series,” Physical review letters, vol. 88, no. 17, p.
 Z. Zhang, X. Guo, and Y. Lin, “Trust management method of d2d
communication based on rf fingerprint identification,” IEEE Access,
vol. 6, pp. 66 082–66 087, 2018.
 C. J. Burges, “A tutorial on support vector machine for pattern
recognition,” Data mining and knowledge discovery, vol. 2, no. 2, pp.
 C.-W. Hsu, C.-C. Chang, C.-J. Lin et al., “A practical guide to support
vector classification,” 2003.