Stochastic analysis of adaptive gradient identification of Wiener-Hammerstein Systems for Gaussian inputs

IEEE Transactions on Signal Processing

Volumn 48, Issue 2, 2000, Pages 557-560

  Bershad, N J ^a   Bouchired, S ^b   Castanie, F ^b  

^a University of California at Irvine   (United States)

^b UNIVERSITÉ DE TOULOUSE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE ALGORITHMS; CONVOLUTION; ERROR ANALYSIS; MATHEMATICAL MODELS; RANDOM PROCESSES; SPURIOUS SIGNAL NOISE;

WIENER-HAMMERSTEIN SYSTEMS (WHS);

SIGNAL PROCESSING;

EID: 0033906390     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.823983     Document Type: Article

References (7)

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2. S. A. Billings, "Identification of nonlinear systems-A survey," Proc. Inst. Elect. Eng., vol. 127, pp. 272-285, 1980.
3. S. A. Billings and S. Y. Fakhouri, "Identification of nonlinear systems using the Wiener model," Electron. Lett., vol. 17, pp. 502-504, 1977.
4. S. Haykin, Adaptive Filter Theory. Englewood Cliffs, NJ: Prentice-Hall, 1991.
5. N. J. Bershad, P. Celka, and J. M. Vesin, "Stochastic analysis of gradient adaptive identification of nonlinear systems with memory for Gaussian data and noisy input and output measurements," IEEE Trans. Signal Processing, vol. 47, pp. 675-689, Mar. 1999.
6. N. J. Bershad, J. J. Shynk, and P. L. Feintuch, "Statistical analysis of the single-layer back-propagation algorithm, Parts I and II," IEEE Trans. Signal Processing, vol. 41, pp. 573-591, Feb. 1993.
7. N. J. Bershad, M. Ibnkahla, and F. Castanie, "Statistical analysis of a two-layer backpropagation algorithm used for modeling memoryless channels: The single neuron case," IEEE Trans. Signal Processing, vol. 45, pp. 747-756, Mar. 1997.