The Literature

[R1] W.  A. Gardner, Statistical Spectral Analysis, Englewood Cliffs, NJ: Prentice-Hall, 1987.

[R2] L. Izzo and A. Napolitano, “The Higher-Order Theory of Generalized Almost Cyclostationary Time Series,”” IEEE Trans. Signal Proc., Vol. 46, No. 11, pp. 2975–2989, Nov. 1998.

[R3] W. A. Brown and H. H. Loomis, Jr., “Digital Implementations of Spectral Correlation Analyzers,” IEEE Trans.  Signal Proc., Vol. 41, No. 2, February 1993, pp. 703–720.

[R4] R. S. Roberts, W. A. Brown, and H. H. Loomis, Jr., “Computationally Efficient Algorithms for Cyclic Spectral Analysis,” IEEE Signal Processing Magazine, April 1991, pp. 38–49.

[R5] W. A. Gardner, “Measurement of Spectral Correlation,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 34, No. 5, pp. 1111–1123, Oct. 1986.

[R6] W. A. Gardner. “Cyclic Wiener Filtering: Theory and Method,” IEEE Trans. Comm., Vol. 40, 1992.

[R7] W. A. Gardner, “The Role of Spectral Correlation in Design and Performance Analysis of Synchronizers,” IEEE Trans. Information Theory, Vol 34, pp. 1089–1095, 1986.

[R8]  A. Napolitano, Generalizations of Cyclostationary Signal Processing: Spectral Analysis and Applications, John Wiley & Sons, Ltd. – IEEE Press, 2012. Print ISBN10: 111997335X ISBN13: 9781119973355, Online ISBN: 9781118437926, doi: 10.1002/9781118437926 .

[R9] A. Napolitano “Cyclostationarity: Limits and Generalizations”, Signal Processing, 2016, in press. doi: 10.1016/j.sigpro.2015.09.013.

[R10] A. Napolitano “Cyclostationarity: New Trends and Applications”, Signal Processing, 2016, in press. doi: 10.1016/j.sigpro.2015.09.011.

[R11] A. Napolitano and I. Perna, “Cyclic Spectral Analysis of the GPS Signal,” Digital Signal Processing, (Elsevier), vol. 33, pp. 13-33, October 2014. doi: 10.1016/j.dsp.2014.06.003.

[R12] A. Napolitano, “Sampling of Spectrally Correlated Processes,” IEEE Transactions on Signal Processing, vol. 59, n. 2, pp. 525-539, February 2011. ISSN: 1053-587X doi: 10.1109/TSP.2010.2090873.

[R13] A. Napolitano and M. Tesauro, “Almost-Periodic Higher-Order Statistic Estimation,”  IEEE Transactions on Information Theory, vol. 57, n. 1, pp. 514-533, January 2011. ISSN: 0018-9448 doi: 10.1109/TIT.2010.2090244.

[R14] A. Napolitano, “Sampling Theorems for Doppler-Stretched Wide-Band Signals,” Signal Processing, vol. 90, n. 7, pp. 2276-2287, July 2010. ISSN: 0165-1684 doi: 10.1016/j.sigpro.2010.02.016.

[R15] A. Napolitano, “Discrete-Time Estimation of Second-Order Statistics of Generalized Almost-Cyclostationary Processes,” IEEE Transactions on Signal Processing, vol. 57, n. 5, pp. 1670-1688, May 2009. ISSN: 1053-587X doi: 10.1109/TSP.2009.2013889.

[R16] A. Napolitano, “Estimation of Second-Order Cross-Moments of Generalized Almost-Cyclostationary Processes”, IEEE Transactions on Information Theory, vol. 53, n. 6, pp. 2204-2228, June 2007. ISSN: 0018-9448 doi: 10.1109/TIT.2007.896868.

[R17] T. Fusco, L. Izzo, A. Napolitano and M. Tanda, “On the Second-Order Cyclostationarity Properties of Long-Code DSSS Signals”, IEEE Transactions on Communications, vol. 54, n. 10, pp. 1741-1746, October 2006. ISSN: 0090-6778 doi: 10.1109/TCOMM.2006.881353.

[R18] W. A. Gardner, A. Napolitano, and L. Paura, “Cyclostationarity: Half a Century of Research,” Signal Processing, vol. 86, n. 4, pp. 639-697, April 2006.ISSN: 0165-1684 doi: 10.1016/j.sigpro.2005.06.016.

[R19] A. Napolitano, “Uncertainty in Measurements on Spectrally Correlated Stochastic Processes”,  IEEE Transactions on Information Theory, Vol. 49, pp. 2172-2191, September 2003. ISSN: 0018-9448 doi: 10.1109/TIT.2003.815768.

[R20] L. Izzo and A. Napolitano, “Sampling of Generalized Almost-Cyclostationary Signals”, IEEE Transactions on Signal Processing, Vol. 51, pp. 1546-1556, June 2003. ISSN: 1053-587X doi: 10.1109/TSP.2003.811236.

[R21] L. Izzo and A. Napolitano, “Linear Time-Variant Transformations of Generalized Almost-Cyclostationary Signals, Part II: Development and Applications”, IEEE Transactions on Signal Processing, Vol. 50, pp. 2962-2975, December 2002. ISSN: 1053-587X doi: 10.1109/TSP.2002.805500.

[R22] L. Izzo and A. Napolitano, “Linear Time-Variant Transformations of Generalized Almost-Cyclostationary Signals, Part I: Theory and Method”, IEEE Transactions on Signal Processing, Vol. 50, pp. 2947-2961, December 2002. ISSN: 1053-587X doi: 10.1109/TSP.2002.805499.

[R23] A. Napolitano and C.M. Spooner, “Cyclic Spectral Analysis of Continuous-Phase Modulated Signals”, IEEE Transactions on Signal Processing, Vol. 49, pp. 30-44, January 2001. ISSN: 1053-587X doi: 10.1109/78.890336.

[R24] A. Napolitano and C.M. Spooner, “Median-Based Cyclic Polyspectrum Estimation”, IEEE Transactions on Signal Processing, Vol. 48, pp. 1462-1466, May 2000. ISSN: 1053-587X doi: 10.1109/78.839992.

[R25] F. Flagiello, L. Izzo and A. Napolitano, “A Computationally Efficient and Interference Tolerant Nonparametric Algorithm for LTI System Identification Based on Higher-Order Cyclic Statistics”, IEEE Transactions on Signal Processing, Vol. 48, pp. 1040-1052, April 2000. ISSN: 1053-587X doi: 10.1109/78.827538.

[R26] L. Izzo and A. Napolitano, “Multirate Processing of Time-Series Exhibiting Higher-Order Cyclostationarity”, IEEE Transactions on Signal Processing, Vol. 46, pp. 429-439, February 1998. ISSN: 1053-587X doi: 10.1109/78.655427.

[R27] L. Izzo and A. Napolitano, “Higher-Order Statistics for Rice’s Representation of Cyclostationary Signals”, Signal Processing, Vol. 56, pp. 279-292, February 1997. ISSN: 0165-1684 doi: 10.1016/S0165-1684(96)00175-2.

[R28] L. Izzo and A. Napolitano, “Higher-Order Cyclostationarity Properties of Sampled Time-Series”, Signal Processing, Vol. 54, pp. 303-307, November 1996. ISSN: 0165-1684 doi: 10.1016/S0165-1684(96)00157-0.

[R29] A. Napolitano, “Cyclic Higher-Order Statistics: Input/Output Relations for Discrete- and Continuous-Time MIMO Linear Almost-Periodically Time-Variant Systems,” Signal Processing, Vol. 42, No. 2, pp. 147-166, March 1995. ISSN: 0165-1684 doi: 10.1016/0165-1684(94)00124-I.

[R30] O. A. Dobre, “Signal Identification for Emerging Intelligent Radios: Classical Problems and New Challenges,” IEEE Instrumentation and Measurement Magazine, Vol. 18, pp. 11-18, April 2015.

[R31] H. Wang, O. A. Dobre, C. Li, and D. Popescu, “Blind Cyclostationarity-Based Symbol Period Estimation for FSK Signals,” IEEE Communications Letters,  May 2015.

[R32] W. Jerjawi, Y. Eldemerdash, and O. A. Dobre, “Second-Order Cyclostationarity-Based Detection of LTE SC-FDMA Signals for Cognitive Radio Systems,” IEEE Transactions on Instrumentation and Measurement, Vol. 64, pp. 823-833, March 2015.

[R33] E. Karami and O. A. Dobre, “Identification of SM-OFDM and AL-OFDM Signals Based on Their Second-Order Cyclostationarity,” IEEE Transactions on Vehicular Technology, Vol. 64, pp. 942-953, March 2015.

[R34] Q. Zhang, O. A. Dobre, Y. Eldemerdash, S. Rajan, and R. Inkol, “Second-Order Cyclostationarity of BT-SCLD Signals: Theoretical Developments and Applications to Signal Classification and Blind Parameter Estimation,” IEEE Transactions on Wireless Communications, Vol. 12, pp. 1501 – 1511, April 2013.

[R35] A. Al-Habashna, O. A. Dobre, R. Venkatesan, and D. C. Popescu, “Second-Order Cyclostationarity of Mobile WiMAX and LTE OFDM Signals and Application to Spectrum Awareness in Cognitive Radio Systems,” IEEE Journal of Selected Topics in Signal Processing, Vol. 6, pp. 26-42, Feb. 2012.

[R36] M. Marey, O. A. Dobre, and R. Inkol, “Classification of Space-Time Block Codes Based on Second-Order Cyclostationarity with Transmission Impairments,” IEEE Transactions on Wireless Communications, Vol. 11, pp. 2574-2584, July 2012.

[R37] O. A. Dobre, M. Oner, S. Rajan, and R. Inkol, “Cyclostationarity-Based Robust Algorithms for QAM Signal Identification,” IEEE Communications Letters, Vol. 16, pp. 12-15, Jan. 2012.

[R38] M. Oner and O. A. Dobre, “On the Second-Order Cyclic Statistics of Signals in the Presence of Receiver Impairments,” IEEE Transactions on Communications, Vol. 59, pp. 3278 -3284, Dec. 2011.

[R39] Punchihewa, Q. Zhang, O. A. Dobre, C. Spooner, S. Rajan, and R. Inkol, “On the Cyclostationarity of OFDM and Single Carrier Linearly Digitally Modulated Signals in Time Dispersive Channels: Theoretical Developments and Application,” IEEE Transactions on Wireless Communications, Vol. 9, pp. 2588 – 2599, August 2010.

[R40] O. A. Dobre, A. Abdi, Y. Bar-Ness, and W. Su, “Cyclostationarity-Based Modulation Classification of Linear Digital Modulations in Flat Fading Channels,” Wireless Personal Communications, Vol. 54, pp. 699-717, Sept. 2010.

[R41] O. A. Dobre, S. Rajan, and R. Inkol, “Joint Signal Detection and
Classification Based on First-Order Cyclostationarity for Cognitive Radios,” EURASIP Journal on Advances in Signal Processing, Special Issue on Dynamic Spectrum Access for Wireless Networking, Vol. 2009, pp. 1-12, July 2009.

[R42] P. J. Daniell, “Discussion of ‘On the Theoretical Specification and Sampling Properties of Autocorrelated Time-Series,'” Journal of the Royal Statistical Society, Vol. 8, pp. 88-90, 1946.

[R43] S. L. Marple, Digital Spectral Analysis with Applications, Prentice-Hall, Englewood Cliffs, NJ, 1987.

[R44] J. Proakis and M. Salehi, Digital Communications, 5th Edition, McGraw-Hill Education, November 2007.

[R45] D. Ramirez et al, “Detection of Multivariate Cyclostationarity,” IEEE Transactions on Signal Processing, Vol. 63, No. 20, pp. 5395-5408, October 2015.

[R46] W. A. Gardner, “Spectral Correlation of Modulated Signals: Part I–Analog Modulation,” IEEE Transactions on Communications, Vol. 35, No. 6, pp. 584-594, June 1987.

[R47] W. A. Gardner, W. A. Brown, and C-K Chen, “Spectral Correlation of Modulated Signals: Part II–Digital Modulation,” IEEE Transactions on Communications, Vol. 35, No. 6, pp. 595-601, June 1987.

[R48] W. A. Gardner and C-K Chen, “Signal-Selective Time-Difference-of-Arrival Estimation for Passive Location of Man-Made Signal Sources in Highly Corruptive Environments, Part I: Theory and Method,” IEEE Transactions on Signal Processing, Vol. 40, No. 5, pp. 1168-1184, May 1992.

[R49] C-K Chen and W. A. Gardner, “Signal-Selective Time-Difference-of-Arrival Estimation for Passive Location of Man-Made Signal Sources in Highly Corruptive Environments, Part I: Algorithms and Performance,” IEEE Transactions on Signal Processing, Vol. 40, No. 5, pp. 1185-1197, May 1992.

[R50] G. Fong, W. A. Gardner, and S. V. Schell, “An Algorithm for Improved Signal-Selective Time-Difference Estimation for Cyclostationary Signals,” IEEE Signal Processing Letters, Vol. 1, No. 2, pp. 38-40, Feb. 1994.

[R51] W. A. Gardner and C-K Chen, “Interference-Tolerant Time-Difference-of-Arrival Estimation for Modulated Signals,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 36, No. 9, pp. 1385-1395, Sept. 1988.

[R52] C. H. Knapp and G. C. Carter, “The Generalized Correlation Method for Estimation of Time Delay,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 24, No. 4, pp. 320-327, August 1976.

[R53] G. C. Carter and A. H. Nutall, “Statistics of the Estimate of Coherence,” IEEE Proceedings (Letters), pp. 465-466, April 1972.

[R54] K. Scarbrough, R. J. Tremblay, and G. C. Carter, “Performance Predictions for Coherent and Incoherent Processing Techniques of Time Delay Estimation,” IEEE Transactions on Acoustics, Speech, and Signal Processing,” Vol. 31, No. 5, pp. 1191-1196, October 1983.

[R55] G. C. Carter, “Time Delay Estimation for Passive Sonar Signal Processing,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 29, No. 3, pp. 463-470, June 1983.

[R56] K. Scarbrough, N. Ahmed, and G. C. Carter, “On the Simulation of a Class of Time Delay Estimation Algorithms,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 29, No. 3, pp. 534-540, June 1981.

[R57] G. C. Carter, A. H. Nutall, and P. G. Cable, “The Smoothed Coherence Transform,” IEEE Proceedings (Letters),” pp. 1497-1498, Oct. 1973.

[R58] G. C. Carter, “Coherence and Time Delay Estimation,” IEEE Proceedings, Vol. 75, No. 2, pp. 236-255, Feb. 1987.

[R59] A. O. Hero and S. C. Schwartz, “A New Generalized Cross Correlator,” IEEE Transactions on Acoustics, Speech, and Signal Processing,” Vol. 33, No. 1, pp. 38-45, Feb. 1985.

[R60] R. L. Kirlin and J. N. Bradley, “Delay Estimation Simulations and a Normalized Comparison of Published Results,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 30, No. 3, pp. 508-511, June 1982.

[R61] C. R. Holt, “Two Channel Likelihood Detectors for Arbitrary Linear Channel Distortion,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 35, No. 3, pp. 267-273, March 1987.

[R62] M. Wax, “The Estimate of Time Delay Between Two Signals with Random Relative Phase Shift,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 29, No. 3, pp. 497-501, June 1981.

[R63] S. Stein, “Algorithms for Ambiguity Function Processing,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 29, No. 3, pp. 588-599, June 1981.

[R64] G. C. Carter, “Receiver operating characteristics for a linearly thresholded coherence estimation detector,” IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 25, Issue 1, pp. 90-92, Feb. 1977.

[R65] W. A. Gardner, “Signal Interception: A Unifying Theoretical Framework for Feature Detection,” IEEE Transactions on Communications, Vol. 36, No. 8, pp. 897-906, August 1988.

[R66] D. E. Reed and M. A. Wickert, “Minimization of Detection of Symbol-Rate Spectral Lines by Delay and Multiply Receivers,” IEEE Transactions on Communications, Vol. 36, No. 1, pp. 118-120, Jan. 1988.

[R67] W. A. Gardner, “Two Alternative Philosophies for Estimation of the Parameters of Time-Series,” IEEE Transactions on Information Theory, Vol. 37, No. 1, pp. 216-218, January 1991.

[R68] W. A. Gardner, “Common Pitfalls in the Application of Stationary Process Theory to Time-Sampled and Modulated Signals,” IEEE Transactions on Communications, Vol. 35, No. 5, pp. 529-534, May 1987.

[R69] E. Rebeiz, F. Yuan, P. Urriza, D. Markovic, and D. Cabric, “Energy-Efficient Processor for Blind Signal Classification in Cognitive Radio Networks,” IEEE Transactions on Circuits and Systems, Vol. 61, No. 2, pp. 587-599, Feb. 2014.

[R70] P. Stoica and R. Moses, Introduction to Spectral Analysis, Prentice-Hall, New Jersey, 1997.

[R71] W. M. Jang, “Blind Cyclostationary Spectrum Sensing in Cognitive Radios,” IEEE Communications Letters, Vol. 18, No. 3, pp. 393-396, March 2014.

[R72] A. Polydoros and K. Kim. “On the Detection and  Classification of Quadrature Digital Modulations in Broad-Band Noise,”  IEEE Transactions on Communications, Vol. 38, pp. 1199–1211, Aug. 1990.

[R73]  C-Y Huang and A. Polydoros. “Likelihood Methods for MPSK  Modulation Classification,” IEEE Transactions on Communications,  Vol. 43, pp. 1493–1504, Feb.–Apr. 1995.

[R74] F. F. Liedtke. “Computer Simulation of an Automatic  Classification Procedure for Digitally Modulated Communication Signals with Unknown Parameters,” Signal Processing, Vol. 6, No. 4, pp.  311–323, Aug. 1984.

[R75]  F. Jondral. “Automatic Classification of High Frequency Signals,” Signal Processing, Vol. 9, No. 3, pp. 177–190, Oct. 1985.

[R76]  R. J. Mammone, R. J. Rothaker, C. I. Podilchuk, S. Davidovici, and D. L. Schilling. “Estimation of Carrier Frequency,  Modulation Type and Bit Rate of an Unknown Modulated Signal,”Proceedings of the International Communications Conference (ICC),
pp. 28.4.1–28.4.7, 1987.

[R77] L. V. Dominguez, J. M. P. Borrallo, and J. P. Garcia. “A General Approach to the Automatic Classification of Radiocommunication Signals,”  Signal Processing, Vol. 22, pp. 239–250, Mar. 1991.

[R78]  J. Aisbett. “Automatic Modulation Recognition Using Time Domain Parameters,”  Signal Processing, Vol. 13, No. 3, pp. 323–328, Oct. 1987.

[R79] Y. T. Chan and L. G. Gadbois. “Identification of the Modulation Type of a Signal,” Signal Processing, Vol. 16, No. 2, pp. 149–154, Feb. 1989.

[R80] J. E. Hipp. “Modulation Classification Based on Statistical Moments,”  Proceedings of MILCOM ’86, pp. 20.2.1–20.2.6, 1986.

[R81] Q. Zhu, M. Kam, and R. Yeager. “Non-Parametric Identification of QAM Constellations in Noise,” Proceedings of ICASSP ’93, pp. IV-184–IV-187, 1993.

[R82] Y. K. Kim and C. L. Weber.  “Generalized Single Cycle Classifier with Applications to SQPSK v.s. $2^k$PSK,”  Proceedings of MILCOM ’89, pp. 46.1.1–46.1.5, 1989.

[R83]  S-Z Hsue and S. S. Soliman. “Automatic Modulation Recognition of Digitally Modulated Signals,” Proceedings of MILCOM ’89 , pp. 37.4.1–37.4.5, 1989.

[R84] S. S. Soliman and S-Z Hsue. “Signal Classification Using Statistical Moments,”  IEEE Transactions on Communications, Vol. 40, pp. 908–916, May 1992.

[R85] B. F. Rice, S. R. Smith, and R. A. Threlkeld. “A Neural Network Classifier for Cyclostationary Signals,”  Proceedings of ICASSP ’94.

[R86] E. E. Azzouz and A. K. Nandi, Automatic Modulation Recognition of Communication Signals, Kluwer Academic, 1996.

[R87] B. G. Mobasseri, “Digital Modulation Classification using Constellation Shape,”  Signal Processing, Vol. 80, pp. 251–277, 2000.

[R88] J. Reichert, “Automatic Classification of Communication Signals using Higher-Order Statistics,”  Proceedings of ICASSP, San Francisco, CA, pp. V-221–V-224, April 1992.

[R89] C. Schreyogg, K. Kittel, and U. Kressel, “Robust Classification of Modulation Types using Spectral Features Applied to HMM,”  Proceedings of MILCOM, Monterey, CA, 1997.

[R90] A. Swami and B. M. Sadler, “Hierarchical Digital Modulation Classification Using Cumulants,” IEEE Transactions on Communications, Vol. 48, No. 3, pp. 416–429, March 2000.

[R91] W. Wei and J. M. Mendel, “A Fuzzy Logic Method for Modulation Classification in Ideal Environments,”  IEEE Transactions on Fuzzy Systems, Vol. 7, No. 3, pp. 333–344, June 1999.

[R92] W. Wei and J. M. Mendel, “Maximum-Likelihood Classification for Digital Amplitude-Phase Modulations,”  IEEE Transactions on Communications, Vol. 48, No. 2, pp. 189–193, February 2000.

[R93] Y. Yang and S. S. Soliman. “An Improved Moment-Based Algorithm for Signal Classification,”  Signal Processing, Vol. 43, pp. 231–244, 1995.

[R94]  Y. Yang and C.-H. Liu. “An Asymptotic Optimal Algorithm for Modulation Classification,”  IEEE Communications Letters, Vol. 2, No. 5, pp. 117–119, May 1998.

[R95] A. Napolitano and M. Tanda, “Blind Parameter Estimation in Multiple-Access Systems,” IEEE Transactions on Communications, Vol. 49, No. 4, pp. 688-698, April 2001.

[R96] M. J. Ready, M. L. Downey, and L. J. Corbalis, “Automatic Noise Floor Spectrum Estimation in the Presence of Signals,” Proceedings of the Thirty-First Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, 1997, pp. 877-881.

[R97] S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications,” IEEE Journal on Selected Areas in Communications, Vol. 23, No. 2, pp. 201-220, Feb. 2005.

[R98] D. J. Thomson, “Spectrum Estimation and Harmonic Analysis,” Proceedings of the IEEE, Vol. 70, No. 9, pp. 1055-1096, Sept. 1982.

[R99] A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet Classification with Deep Convolution Neural Networks,” Advances in Neural Information Processing Systems 25, F. Pereira Editor, 2012, pp. 1097–1105. Also https://www.nvidia.cn/content/tesla/pdf/machine-learning/ImageNet-classification-with-deep-Convolutional-nn.pdf.

[R100] T. O’Shea, K. Karra, and T. Clancy, “Learning Approximate Neural Estimators for Wireless Channel State Information,” arXiv Post, https://arXiv.org/abs/1707.06260, July 2017.

[R101] S. Horstmann, D. Ramírez, and P. J. Schreier, “Detection of Almost-Cyclostationarity: An Approach Based on a Multiple Hypothesis Test,” Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, 2017, pp. 1635-1639.

[R102] B. G. Agee, S. V. Schell, and W. A. Gardner, “Spectral Self-Coherence Restoral – A New Approach to Blind Adaptive Signal Extraction using Antenna Arrays,” Proceedings of the IEEE, Vol. 78, No. 4, April 1990, pp. 753-767.

[R103] S. V. Schell and W. A. Gardner, “Blind Adaptive Spatiotemporal Filtering for Wide-band Cyclostationary Signals,” IEEE Transactions on Signal Processing, Vol. 41, No. 5, pp. 1961-1964, May 1993.

[R104] S. V. Schell, “Performance Analysis of the Cyclic MUSIC Method of Direction Estimation for Cyclostationary Signals,” IEEE Transactions on Signal Processing, Vol. 42, No. 11, pp. 3043-3050, Nov. 1994.

[R105] S. V. Schell and W. A. Gardner, “The Cramer-Rao Lower Bound for Directions of Arrival of Gaussian Cyclostationary Signals,” IEEE Transactions on Information Theory, Vol. 38, No. 4, pp. 1418-1422, July 1992.

[R106] S. V. Schell, “Exploitation of Spectral Correlation for Signal-Selective Direction Finding,” Doctoral Dissertation, Department of Electrical and Computer Engineering, UC Davis, 1990.

[R107] J. Antoni, “Cyclostationarity by Examples,” Mechanical Systems and Signal Processing, Vol. 23, pp. 987-1036, 2009.

[R108] E. Estupinan, P. White, and C. San Martin, “A Cyclostationary Analysis Applied to Detection and Diagnosis of Faults in Helicopter Gearboxes,” L. Rueda, D. Mery, and J. Kittler (Eds.): CIARP 2007, LNCS 4756, pp. 61–70, 2007.

[R109] Z. Ma et al, “Cyclostationary Analysis of a Faulty Bearing in the Wind Turbine,” Journal of Solar Energy Engineering,  Vol. 139, June 2017.

[R110] W. A. Gardner, “A New Method of Channel Identification,” IEEE Transactions on Communications, Vol. 39, No. 6, pp. 813-817, June 1991.

[R111] R. W. Heath and G. B. Giannakis, “Exploiting Input Cyclostationarity for Blind Channel Identification in OFDM Systems,” IEEE Transactions on Signal Processing, Vol. 47, No. 3, pp. 848-856, March 1999.

[R112] A. Chevreuil and P. Loubaton, “MIMO Blind Second-Order Equalization Method and Conjugate Cyclostationarity,” IEEE Transactions on Signal Processing, Vol. 47, No. 2, pp. 572-578, Feb. 1999.

[R113] L. A. Baccala and S. Roy, “A New Blind Time-Domain Channel Identification Method Based on Cyclostationarity,” IEEE Signal Processing Letters, Vol. 1, No. 6, pp. 89-91, June 1994.

[R114] Ye Li and Zhi Ding, “ARMA System Identification Based on Second-Order Cyclostationarity,” IEEE Transactions on Signal Processing, Vol. 42, No. 12, pp. 3483-3494, Dec. 1994.

[R115] Zhi Ding and Y. Li, “On Channel Identification Based on Second-Order Cyclic Spectra,” IEEE Transactions on Signal Processing, Vol. 42, No. 5, pp. 1260-1264, May 1994.

[R116] P. Ciblat, E. Serpedin, and Y. Wang, “On a Blind Fractionally Sampling-Based Carrier Frequency Offset Estimator for Noncircular Transmissions,” IEEE Signal Processing Letters, Vol. 10, No. 4, pp. 89-92, April 2003.

[R117] M. Moeneclaey, “Linear Phase-Locked Loop Theory for Cyclostationary Input Disturbances,” IEEE Transactions on Communications, Vol. 30, No. 10, pp. 2253-2259, October 1982.

[R118] Y. Wang, E. Serpedin, and P. Ciblat, “An Alternative Blind Feedforward Symbol Timing Estimator Using Two Samples Per Symbol,” IEEE Transactions on Communications, Vol. 51, No. 9, pp. 1451-1455, September 2003.

[R119] Y. Wang, P. Ciblat, E. Serpedin, and P. Loubaton, “Performance Analysis of a Class of Nondata-Aided Frequency Offset and Symbol Timing Estimators for Flat-Fading Channels,” IEEE Transactions on Signal Processing, Vol. 50, No. 9, pp. 2295-2305, September 2002.

[R120] J. A. Lopez-Salcedo and G. Vazquez, “Asymptotic Equivalence Between the Unconditional Maximum Likelihood and the Square-Law Nonlinearity Symbol Timing Estimation,” IEEE Transactions on Signal Processing, Vol. 54, No. 1, pp. 244-257, January 2006.

[R121] F. Gini and G. B. Giannakis, “Frequency Offset and Symbol Timing Recovery for Flat-Fading Channels: A Cyclostationary Approach,” IEEE Transactions on Communications, Vol. 46, No. 3, pp. 400-411, March 1998.

[R122] H. Bolcskei, “Blind Estimation of Symbol Timing and Carrier Frequency Offset in Wireless OFDM,” IEEE Transactions on Communications, Vol. 49, No. 6, pp. 988-999, June 2001.

[R123] A. Fontes, J. Rego, A. Martins, L. Silveira,  and J. Principe, “Cyclostationary Correntropy: Definition and Applications,” Expert Systems with Applications, Vol. 69. 2016.

[R124] T. Liu, T. Qiu, and S. Luan, “Cyclic Correntropy: Foundations and Theories,” IEEE Access, Vol. 6, pp. 34659-34669, 2018.

[R125] Yang Liu, Yinghui Zhang, Tianshuang Qiu, Jing Gao, Shun Na, “Improved Time Difference of Arrival Estimation Algorithms for Cyclostationary Signals in α-Stable Impulsive Noise,” Digital Signal Processing, Vol. 76, pp. 94-105, 2018.

[R126] Shengyang Luan, Tianshuang Qiu, Yongjie Zhu, Ling Yu, “Cyclic correntropy and its spectrum in frequency estimation in the presence of impulsive noise,” Signal Processing, Vol. 120, pp. 503-508, 2016.

[R127] T. Liu, T. Qiu, F. Jin, S. Wilcox and S. Luan, “Phased Fractional Lower-Order Cyclic Moment Processed in Compressive Signal Processing,” IEEE Access, vol. 7, pp. 98811-98819, 2019.

[R128] O. Yeste-Ojeda and J. Grajal, “Detection of Unknown Signals Based on Spectral Correlation Measurements,” European Signal Processing Conference (EUSIPCO), Florence, Italy, September 2006.

[R129] O. Yeste-Ojeda and J. Grajal, “Limitations of Spectral Correlation Based Detectors,” IEEE/SP 14th Workshop on Statistical Signal Processing, Madison, WI, USA, 2007, pp. 244-248.

[R130] O. Yeste-Ojeda and J. Grajal, “Sensitivity Analysis of Cyclostationarity-Based and Radiometric Detectors for Single-Sensor Receivers,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 48, No. 1, pp. 27-43, January 2012.

[R131] A. Napolitano, Cyclostationary Processes and Time Series: Theory, Applications, and Generalizations, Academic Press, ISBN-13: 978-0081027080, 2019.

[R132] C. D. McGillem and G. R. Cooper, Continuous and Discrete Signal and System Analysis, Holt, Rinehart, and Winston, New York, 1974.

[R133] J. Sun, G. Wang, Z. Lin, S. G. Razul, and X. Lai, “Automatic Modulation Classification of Cochannel Signals using Deep Learning,” IEEE 23rd International Conference on Digital Signal Processing, November, 2018.

[R134] D. Zhang, W. Ding, C. Liu, H. Wang, and B. Zhang, “Modulated Autocorrelation Convolution Networks for Automatic Modulation Classification Based on Small Sample Set,” IEEE Access, February 2020.

[R135] M. Kulin, T. Kazaz, I. Moerman, and E. do Poorter, “End-to-End Learning from Spectrum Data: A Deep Learning Approach for Wireless Signal Identification in Spectrum Monitoring Applications,” arXiv Post, December 2017.

[R136] S. Rajendran, W. Meert, D. Giustiniano, V. Lenders, and S. Pollin, “Deep Learning Models for Wireless Signal Classification with Distributed Low-Cost Spectrum Sensors,” arXiv Post, July 2018.

[R137] T. O’Shea, T. Roy, and T. C. Clancy, “Over the Air Deep Learning Based Radio Signal Classification,” arXiv Post, December 2017.

[R138] T. O’Shea and J. Corgan, “Convolutional Radio Modulation Recognition Networks,” arXiv Post, February 2016.

[R139] T. O’Shea, N. West, M. Vondal, and T. Clancy, “Semi-Supervised Radio Signal Identification,” arXiv Post, November 2016.

[R140] T. O’Shea and J. Hoydis, “An Introduction to Machine Learning Communication Systems,” arXiv Post, February 2017.

[R141] J. Yu, M. Alhassoun, and R. M. Buehrer, “Interference Classification Using Deep Neural Networks,” arXiv Post, February 2020.

[R142] X. Liu, D. Yang, and A. E. Gamal, “Deep Neural Network Architectures for Modulation Classification,” Proceedings of the Asilomar Conference on Signals, Systems, and Computers, Nov. 2017.

[R143] S. Ramjee, et al, “Fast Deep Learning for Automatic Modulation Classification,” arXiv Post, January 2019.

[R144] W. M. Jang, “Simultaneous Power Harvesting and Cyclostationary Spectrum Sensing in Cognitive Radios,” in IEEE Access, vol. 8, pp. 56333-56345, 2020. (https://ieeexplore.ieee.org/document/9042338)

[R145] W. A. Gardner, “Exploitation of Spectral Redundancy in Cyclostationary Signals,” IEEE Signal Processing Magazine, Vol. 8, No. 2, pp. 14-36, April 1991.

[R146] K. Bu, Y. He, X. Jing and J. Han, “Adversarial Transfer Learning for Deep Learning Based Automatic Modulation Classification,” IEEE Signal Processing Letters, May 2020, doi: 10.1109/LSP.2020.2991875.

[R147] A. Smith, M. Evans and J. Downey, “Modulation classification of satellite communication signals using cumulants and neural networks,” 2017 Cognitive Communications for Aerospace Applications Workshop (CCAA), Cleveland, OH, 2017, pp. 1-8, doi: 10.1109/CCAAW.2017.8001878.

[R148] B. Hamdaoui, A. Elmaghbub, and S. Mejri, “Deep Neural Network Feature Designs for RF Data-Driven Wireless Device Classification,” IEEE Network, November 2020.

[R149] G. R. Cooper and C. D. McGillem, Probabilistic Methods of Signal and System Analysis, Holt, Rinehart, and Winston, New York, NY, 1971.

[R150] W. A. Gardner, “A unifying view of coherence in signal processing,” Signal Processing, Vol. 29, No. 2, 1992, pp. 113-140.

[R151] W. A. Gardner, “The Spectral Correlation Theory of Cyclostationary Time-Series,” EURASIP Signal Processing, Vol. 11, pp. 13-36, 1986.

[R152] J. Antoni, G. Xin, and N. Hamzaoui, “Fast Computation of the Spectral Correlation,” Mechanical Systems and Signal Processing, Vol. 92, 2017, pp. 248-277.

[R153] A. B. Carlson and P. B. Crilly, Communication Systems: An Introduction to Signals and Noise in Electrical Communication, Fifth Edition, McGraw-Hill Higher Education, 2010.

[R154] G. R. Cooper and C. D. McGillem, Modern Communications and Spread Spectrum, McGraw-Hill Series in Electrical Engineering, 1986.

[R155] C. Candan, “Proper Definition and Handling of Dirac Delta Functions,” IEEE Signal Processing Magazine, May 2021, pp. 186-203.

[R156] W. A. Gardner, Introduction to Random Processes, With Applications to Signals & Systems, Second Edition, McGraw-Hill, 1990.

[R157] D. T. Kawamotot and R. W. McGwier, “Rigorous Moment-Based Automatic Modulation Classification,” Proceedings of the Sixth Gnu-Radio Conference, 2016.

[R158] T. J. O’Shea, T. C. Clancy, and H. J. Ebeid, “Practical Signal Detection and Classification in Gnu Radio,” Proceedings of the SDR Forum, 2007.

[R159] N. Bitar, S. Muhammad, and H. Refai, “Wireless Technology Identification Using Deep Convolutional Neural Networks,” 28th Annual IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications, 2017.

[R160] C. de Vrieze, L. Simic, and P. Mahonen, “The Importance of Being Earnest: Performance of Modulation Classification for Real RF Signals,” arXiv.org, IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN), 2018.

[R161] Z. Xu et al, “Identification of Communication Signals Using Learning Approaches for Cognitive Radio Applications,” IEEE Access, 2020.

[R162] X. Li et al, “A Survey on Deep Learning Techniques in Wireless Signal Recognition,” Wireless Communication and Mobile Computing, Vol. 2019, 2019.

[R163] T. O’Shea, K. Karra, and T. C. Clancy, “Learning Approximate Neural Estimators for Wireless Channel State Information,” IEEE International Workshop on Machine Learning for Signal Processing, 2017.

[R164] R. Sahay, C. G. Brinton, and D. J. Love, “Frequency-Based Automated Modulation Classification in the Presence of Adversaries,” arXiv.org, 2021.

[R165] S. Zhou et al, “A Robust Modulation Classification Method Using Convolutional Neural Networks,” EURASIP Journal on Advances in Signal Processing, 2019.

[R166] N. Soltani et al, “Spectrum Awareness at the Edge: Modulation Classification Using Smartphones,” IEEE International Symposium on Dynamic Spectrum Access Networks, 2019.

[R167] N. Soltani et al, “More is Better: Data Augmentation for Channel-Resiliant RF Fingerprinting,” IEEE Communication Magazine, October 2020.

[R168] A. Ivanov et al, “Deep Learning for Modulation Classification: Signal Features in Performance Analysis,” Joint Conference on Digital Arts, Media, and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer, and Telecommunication Engineering, 2020.

[R169] X. Shang et al, “Dive into Deep Learning Based Automatic Modulation Classification: A Disentangled Approach,” IEEE Access, 2016.

[R170] V. Sathyanarayanan et al, “Modulation Classification Using Neural Networks,” UCSD NoiseLab Internal Report, http://noiselab.ucsd.edu/ECE228_2019/Reports/Report42.pdf, 2019.

[R171] Y. Xue et al, “Co-Channel Modulation Recognition Based on Deep Learning,” International Conference on Wireless Communications and Signal Processing, October 2020, pp. 563-568.

[R172] P. Borghesani and J. Antoni, “A Faster Algorithm for the Calculation of the Fast Spectral Correlation,” Mechanical Systems and Signal Processing (Elsevier), No. 111, 2018, pp. 113-118.

[R173] S. Luan, J. Li, Y. Gao, and T. Qiu, “Cyclic Correntropy: Properties and the Application in Symbol Rate Estimation Under Alpha-Stable Distributed Noise,” Digital Signal Processing (Elsevier), February, 2022.

[R174] T. Oyedare, V. Shah, D. Jakubisin, and J. Reed, “Interference Suppression Using Deep Learning: Current Approaches and Open Challenges,” arxiv.org, https://arxiv.org/abs/2112.08988, December 16, 2021.

[R175]. L. Smolin, The Trouble with Physics, Boston: Houghton Mifflin, 2006.

[R176] N. West, T. Roy, and T. O’Shea, “Wideband Signal Localization with Spectral Segmentation,” arxiv.org, October 2021.

[R177] F. Wei et al, “Detection of Direct Sequence Spread Spectrum Signals Based on Deep Learning,” IEEE Transactions on Cognitive Communications and Networking, doi: 10.1109/TCCN.2022.3174609 (Accepted For Publication).

[R178] T. Yucek and H Arslan, “A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications,” IEEE Communications Surveys & Tutorials, Vol. 11, No. 1, 2009.

[R179] P. Mathys, “Efficient band occupancy and modulation parameter
detection,” Proceedings of the GNU Radio Conference, Vol. 2, No. 1, 2017. Available: https://pubs.gnuradio.org/index.php/grcon/article/view/36

[R180] S. Lin, Y. Zeng, and Y. Gong, “Modulation Recognition Using Signal Enhancement and Multi-Stage Attention Mechanism,” IEEE Transactions on Wireless Communications, Accepted for Publication in 2022.

[R181] G. Zoumpourlis, A. Doumanoglou, N. Vretos, and P. Daras, “Non-linear Convolution Filters for CNN-Based Learning,” 2017 IEEE International Conference on Computer Vision (ICCV), 2017, pp. 4771-4779. arXiv:1708.07038 [cs.CV]

[R182] L. Hong, “Classification of BPSK and QPSK Signals in Fading Environment using the ICA Technique,” in Southeastern Symposium on System
Theory (SSST)
, 2005.

[R183] X. Liu et al, “Wireless Signal Representation Techniques for Automatic Modulation Classification,” IEEE Access, (Accepted 2022), DOI 10.1109/ACCESS.2022.3197224.

[R184] B. Widrow, J. McCool, and M. Ball, “The Complex LMS Algorithm,” Proceedings of the IEEE, April 1975, pp. 719-720.

[R185] H. W. J. Rittel and M. M. Webber, “Dilemmas in a General Theory of Planning” 1973 (PDF). Policy Sciences. 4 (2): 155–169. doi:10.1007/bf01405730. S2CID 18634229. Archived from the original (PDF) on 30 September 2007. [Reprinted in Cross, N., ed. (1984). Developments in Design Methodology. Chichester, England: John Wiley & Sons. pp. 135–144.].

[R186] J. Conklin, Dialogue Mapping: Building Shared Understanding of Wicked Problems. Chichester, England: Wiley. ISBN 978-0-470-01768-5, 2006.

[R187] L. Boegner, G. Vanhoy, P. Vallance, M. Gulati, D. Feitzinger, B. Comar, R. D. Miller, “Large Scale Radio Frequency Wideband Signal Detection & Recognition,” https://arxiv.org/abs/2211.10335, 2022.

[R188] T. Aulin and C. W. Sundberg, “Continuous Phase
Modulation–Part I: Full Response Signaling,” IEEE Transactions on
Communications
, Vol. 29, pp. 196–209, March 1981.

[R189] T. Aulin, N. Rydbeck, and C. W. Sundberg, “Continuous Phase
Modulation–Part II: Partial Response Signaling,” IEEE Transactions on
Communications
, Vol. 29, pp. 210–225, March 1981.

[R190] J. B. Anderson, T. Aulin, C. W. Sundberg, Digital Phase Modulation,
Springer: Applications of Communications Theory, 1986.

[R191] M. Mitchell, Artificial Intelligence: A Guide for Thinking Humans, Picador, New York, 2019.

[R192] T. Karp and N. J. Fliege, “Modified DFT Filterbanks with Perfect Reconstruction,” IEEE Transactions on Circuits and Systems, Vol 46, No. 11, pp. 1404–1414, Nov. 1999.

[R193] T. Karp and N. J. Fliege, “Computationally Efficient Realization of mDFT Filterbanks,” Proceedings of the EURASIP, Trieste, Italy, pp. 1183–1186,
Sept. 1996.

[R194] N. J. Fliege, “Computational Efficiency of Modified DFT Polyphase Filterbanks,” Proceedings of the 27th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, pp. 1296–1300, Nov. 1993.

[R195] M. Soto-Bajo, A. F. Collar and J. Herrera-Vega, “On the Concept of Frequency in Signal Processing: A Discussion [Perspectives],” IEEE Signal Processing Magazine, Vol. 40, No. 6, pp. 18-25, September 2023.

3 thoughts on “The Literature”

  1. Morning Chad,

    I was perusing Dr. Gardner’s blog this morning. He included a link to the entire first edition of his book. I think I recall somewhere in the comments of one of your posts where someone was thinking about purchasing the book, so I thought your blog readers might appreciate saving a few bucks.

    I assume he has checked the box on the usual warning in the front cover requiring the “permission in writing from the publisher” …

    Thank you so much for your blog.

    1. Tom! Welcome to the CSP Blog, my old friend.

      ***

      Chad: Hello, my name is Chad and I’m a recovering SSPIer.
      Support Group: Hello Chad!
      Chad: I’ve been SSPI-free for 23 years, and let me tell you, it feels great!
      SG: [Enthusiastic Applause]
      Chad: But I’m here to tell the story of when I hit rock bottom. It all began when a young promising engineer named Tom and I tried to generalize the Viterbi Algorithm …
      SG: [Gasps]

      ***

      Yeah, I haven’t cited any of your CSP work on the CSP Blog, and I’m sorry for that omission. In my defense, I’ve only been writing about things I understand. Heh. But I do have draft posts of some of the array-processing stuff in CSP (SCORE, Cyclic MUSIC) and at that time I will also point to your 90s work. Looking at your Google Scholar page, I see that is a teensy eensy weensy fraction of your prodigious output! Congratulations on a strong academic career!

Leave a Comment, Ask a Question, or Point out an Error