A signal processing framework based on dynamic neural networks with application to problems in adaptation, filtering, and classification
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[1] B. Anderson,et al. Optimal Filtering , 1979, IEEE Transactions on Systems, Man, and Cybernetics.
[2] S. Haykin,et al. Adaptive Filter Theory , 1986 .
[3] Sharad Singhal,et al. Training Multilayer Perceptrons with the Extende Kalman Algorithm , 1988, NIPS.
[4] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[5] Kumpati S. Narendra,et al. Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.
[6] Paul J. Werbos,et al. Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.
[7] Ronald J. Williams,et al. Adaptive state representation and estimation using recurrent connectionist networks , 1990 .
[8] Jing Peng,et al. An Efficient Gradient-Based Algorithm for On-Line Training of Recurrent Network Trajectories , 1990, Neural Computation.
[9] Peter R. Conwell,et al. Fixed-weight networks can learn , 1990, 1990 IJCNN International Joint Conference on Neural Networks.
[10] Lee A. Feldkamp,et al. Decoupled extended Kalman filter training of feedforward layered networks , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[11] N. E. Cotter,et al. Learning algorithms and fixed dynamics , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[12] Ronald J. Williams,et al. Training recurrent networks using the extended Kalman filter , 1992, [Proceedings 1992] IJCNN International Joint Conference on Neural Networks.
[13] Lee A. Feldkamp,et al. Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks , 1994, IEEE Trans. Neural Networks.
[14] T. Kailath,et al. A state-space approach to adaptive RLS filtering , 1994, IEEE Signal Processing Magazine.
[15] G. V. Puskorius,et al. Training of robust neural controllers , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.
[16] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[17] Christopher M. Bishop,et al. Neural networks for pattern recognition , 1995 .
[18] Lee A. Feldkamp,et al. Dynamic neural network methods applied to on-vehicle idle speed control , 1996, Proc. IEEE.
[19] Lee A. Feldkamp,et al. Adaptation from fixed weight dynamic networks , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).
[20] Lee A. Feldkamp,et al. Adaptive Behavior from Fixed Weight Networks , 1997, Inf. Sci..
[21] Johan A. K. Suykens,et al. NLq theory: checking and imposing stability of recurrent neural networks for nonlinear modeling , 1997, IEEE Trans. Signal Process..
[22] Lee A. Feldkamp,et al. Extensions and enhancements of decoupled extended Kalman filter training , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).
[23] Nazeeh Aranki,et al. Custom VLSI ASIC for automotive applications with recurrent networks , 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).
[24] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .