Volterra series (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Volterra series" in English language version.

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Friston, K.J.; Harrison, L.; Penny, W. (2 April 2003). "Dynamic causal modelling". NeuroImage. 19 (4): 1273–1302. doi:10.1016/S1053-8119(03)00202-7. PMID 12948688. Retrieved 24 April 2024.
S. Orcioni; M. Pirani; C. Turchetti (2005). "Advances in Lee–Schetzen method for Volterra filter identification". Multidimensional Systems and Signal Processing. 16 (3): 265–284. doi:10.1007/s11045-004-1677-7. S2CID 57663554.
Orcioni, Simone (2014). "Improving the approximation ability of Volterra series identified with a cross-correlation method". Nonlinear Dynamics. 78 (4): 2861–2869. doi:10.1007/s11071-014-1631-7.
Korenberg, M. J.; Bruder, S. B.; McIlroy, P. J. (1988). "Exact orthogonal kernel estimation from finite data records: extending Wiener's identification of nonlinear systems". Ann. Biomed. Eng. 16 (2): 201–214. doi:10.1007/BF02364581. PMID 3382067. S2CID 31320729.
Franz, Matthias O.; Bernhard Schölkopf (2006). "A unifying view of Wiener and Volterra theory and polynomial kernel regression". Neural Computation. 18 (12): 3097–3118. doi:10.1162/neco.2006.18.12.3097. PMID 17052160. S2CID 9268156.
J. L. van Hemmen; W. M. Kistler; E. G. F. Thomas (2000). "Calculation of Volterra Kernels for Solutions of Nonlinear Differential Equations". SIAM Journal on Applied Mathematics. 61 (1): 1–21. doi:10.1137/S0036139999336037. hdl:11370/eda737ae-40d1-4ff3-93d7-6b2434d23d52.

Wiener N: Response of a nonlinear device to noise. Radiation Lab MIT 1942, restricted. report V-16, no 129 (112 pp). Declassified Jul 1946, Published as rep. no. PB-1-58087, U.S. Dept. Commerce. URL: http://www.dtic.mil/dtic/tr/fulltext/u2/a800212.pdf

Friston, K.J.; Harrison, L.; Penny, W. (2 April 2003). "Dynamic causal modelling". NeuroImage. 19 (4): 1273–1302. doi:10.1016/S1053-8119(03)00202-7. PMID 12948688. Retrieved 24 April 2024.
Korenberg, M. J.; Bruder, S. B.; McIlroy, P. J. (1988). "Exact orthogonal kernel estimation from finite data records: extending Wiener's identification of nonlinear systems". Ann. Biomed. Eng. 16 (2): 201–214. doi:10.1007/BF02364581. PMID 3382067. S2CID 31320729.
Franz, Matthias O.; Bernhard Schölkopf (2006). "A unifying view of Wiener and Volterra theory and polynomial kernel regression". Neural Computation. 18 (12): 3097–3118. doi:10.1162/neco.2006.18.12.3097. PMID 17052160. S2CID 9268156.

Friston, K.J.; Harrison, L.; Penny, W. (2 April 2003). "Dynamic causal modelling". NeuroImage. 19 (4): 1273–1302. doi:10.1016/S1053-8119(03)00202-7. PMID 12948688. Retrieved 24 April 2024.

S. Orcioni; M. Pirani; C. Turchetti (2005). "Advances in Lee–Schetzen method for Volterra filter identification". Multidimensional Systems and Signal Processing. 16 (3): 265–284. doi:10.1007/s11045-004-1677-7. S2CID 57663554.
Korenberg, M. J.; Bruder, S. B.; McIlroy, P. J. (1988). "Exact orthogonal kernel estimation from finite data records: extending Wiener's identification of nonlinear systems". Ann. Biomed. Eng. 16 (2): 201–214. doi:10.1007/BF02364581. PMID 3382067. S2CID 31320729.
Franz, Matthias O.; Bernhard Schölkopf (2006). "A unifying view of Wiener and Volterra theory and polynomial kernel regression". Neural Computation. 18 (12): 3097–3118. doi:10.1162/neco.2006.18.12.3097. PMID 17052160. S2CID 9268156.

Gibiino, Gian Piero (2016). NONLINEAR CHARACTERIZATION AND MODELING OF RADIO-FREQUENCY DEVICES AND POWER AMPLIFIERS WITH MEMORY EFFECTS (PDF) (PhD thesis). UNIVERSITA DI BOLOGNA. p. 20. Docket lirias1734386. Retrieved 2024-11-26.