과제정보
연구 과제 주관 기관 : Kunsan National University
참고문헌
- A. F. Atiya and A. G.Parlos, "New results on recurrent network training: Unifying the algorithms and accelerating convergence," IEEE Transactions on Neural Networks, vol.11, pp.697-709,May 2000. https://doi.org/10.1109/72.846741
- G.. Kechriotis, E. Zervas, and E. S. Manolakos, "Using recurrent neural networks for adaptive communication channel equalizations," IEEE Transactions on Neural Networks, vol.5, pp.267-278,March 1994. https://doi.org/10.1109/72.279190
- J.S. Choi, M. Bouchard and T. H. Yeap, "Decision Feedback Recurrent Neural Equalization with Fast Convergence Rate," IEEE transactions on Neural Networks, vol. 16, No. 3, May 2005.
- R. J. Williams and D. Zipser, "A learning algorithm for continually running fully recurrent neural networks, "Neural Computation, vol. 1, pp. 270-280, 1989. https://doi.org/10.1162/neco.1989.1.2.270
- S. Julier, J. Uhlmann, and H. F. Durrant-Whyte, "A new method for the nonlinear transformation of means and covariances in filters and estimators," IEEE Transactions on Automatic Control, vol. 45, pp. 477-482, March 2000. https://doi.org/10.1109/9.847726
- S. J. Julier and J. K. Uhlmann, "A new extension of the Kalman filter to nonlinear systems," in Proceedings of Aerospace: The 11th International Symposium on Aerospace/Defence Sensing, Simulation and Controls, 1997.
- S. Haykin, Neural Networks: a comprehensive Foundation, 2nd Ed. Upper Saddle River, NJ: Prentice Hall, 1999.
- E. A. Wan and R. van der Merwe, "The unscented Kalman filter," in Kalman Filtering and Neural Networks, Edited by S.Haykin. John Wiley and Sons, Inc., 2001.
- S. Haykin, Adaptive Filter Theory, 4th Ed. Upper Saddle River, NJ: Prentice Hall, 2002.
- C. Cowan and S. Semnani, "Time-variant equalization using a novel non-linear adaptive structure," International Journal of Adaptive Control and Signal Processing, vol. 12, no. 2, pp. 195- 206, 1998. https://doi.org/10.1002/(SICI)1099-1115(199803)12:2<195::AID-ACS487>3.0.CO;2-K
- O.S. Kwon, J. S. Choi, M. Bouchard and T.H. Yeap, "A Derivative-Free Kalman Filter for Parameter Estimation of Recurrent Neural Networks and Its Applications to Nonlinear Channel Equalization,"4th international ICSC Symposium on EIS 2004.