Introducing the Orthogonal Periodic Sequences for the Identification of Functional Link Polynomial Filters
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[1] M. Korenberg,et al. Exact orthogonal kernel estimation from finite data records: Extending Wiener's identification of nonlinear systems , 1988, Annals of Biomedical Engineering.
[2] Simone Orcioni,et al. Identification of Volterra Models of Tube Audio Devices using Multiple-Variance Method , 2018, Journal of the Audio Engineering Society.
[3] George-Othon Glentis,et al. Efficient algorithms for the solution of block linear systems with Toeplitz entries , 1993 .
[4] Giovanni L. Sicuranza,et al. Perfect periodic sequences for Legendre nonlinear filters , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).
[5] Giovanni L. Sicuranza,et al. Legendre nonlinear filters , 2015, Signal Process..
[6] Nithin V. George,et al. Design of dynamic linear-in-the-parameters nonlinear filters for active noise control , 2016, 2016 24th European Signal Processing Conference (EUSIPCO).
[7] Giovanni L. Sicuranza,et al. Perfect periodic sequences for identification of even mirror fourier nonlinear filters , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[8] W. Rudin. Principles of mathematical analysis , 1964 .
[9] Alberto Carini,et al. Orthogonal LIP Nonlinear Filters , 2018 .
[10] Y. W. Lee,et al. Measurement of the Wiener Kernels of a Non-linear System by Cross-correlation† , 1965 .
[11] Simone Orcioni,et al. Perfect periodic sequences for nonlinear Wiener filters , 2016, 2016 24th European Signal Processing Conference (EUSIPCO).
[12] Giovanni L. Sicuranza,et al. Nonlinear system identification using quasi-perfect periodic sequences , 2016, Signal Process..
[13] V. J. Mathews,et al. Polynomial Signal Processing , 2000 .
[14] Suleyman Serdar Kozat,et al. A Comprehensive Approach to Universal Piecewise Nonlinear Regression Based on Trees , 2014, IEEE Transactions on Signal Processing.
[15] Aníbal R. Figueiras-Vidal,et al. Adaptive Combination of Volterra Kernels and Its Application to Nonlinear Acoustic Echo Cancellation , 2011, IEEE Transactions on Audio, Speech, and Language Processing.
[16] C. Antweiler. Multi‐Channel System Identification with Perfect Sequences – Theory and Applications – , 2008 .
[17] Andrzej Milewski,et al. Periodic Sequences with Optimal Properties for Channel Estimation and Fast Start-Up Equalization , 1983, IBM J. Res. Dev..
[18] Steven Roman. The Umbral Calculus , 1984 .
[19] Walter Kellermann,et al. Recent Advances on LIP Nonlinear Filters and Their Applications , 2018 .
[20] Vasilis Z. Marmarelis,et al. Nonlinear Dynamic Modeling of Physiological Systems , 2004 .
[21] Simone Orcioni,et al. Improving the approximation ability of Volterra series identified with a cross-correlation method , 2014 .
[22] Alberto Carini,et al. Fourier nonlinear filters , 2014, Signal Process..
[23] M. Schetzen,et al. Nonlinear system modeling based on the Wiener theory , 1981, Proceedings of the IEEE.
[24] Yuriy V. Zakharov,et al. A low-complexity RLS-DCD algorithm for volterra system identification , 2016, 2016 24th European Signal Processing Conference (EUSIPCO).
[25] Giovanni L. Sicuranza,et al. Perfect periodic sequences for even mirror Fourier nonlinear filters , 2014, Signal Process..
[26] Giovanni L. Sicuranza,et al. A study about Chebyshev nonlinear filters , 2016, Signal Process..
[27] H. D. Luke,et al. Sequences and arrays with perfect periodic correlation , 1988 .