Bibliography

1

S. J. Julier and J. K. Uhlmann.
A New Extension of the Kalman Filter to Nonlinear Systems.
In Proc. of AeroSense: The 11th Int. Symp. on Aerospace/Defence Sensing, Simulation and Controls., 1997.

2

Eric A. Wan, Rudolph van der Merwe, and Alex T. Nelson.
Dual Estimation and the Unscented Transformation.
In S.A. Solla, T.K. Leen, and K.-R. Müller, editors, Advances in Neural Information Processing Systems 12, pages 666-672. MIT Press, 2000.

3

Simon Haykin.
Adaptive Filter Theory.
Prentice-Hall, Inc, 3 edition, 1996.

4

S. Singhal and L. Wu.
Training multilayer perceptrons with the extended Kalman filter.
In Advances in Neural Information Processing Systems 1, pages 133-140, San Mateo, CA, 1989. Morgan Kauffman.

5

G.V. Puskorius and L.A. Feldkamp.
Decoupled Extended Kalman Filter Training of Feedforward Layered Networks.
In IJCNN, volume 1, pages 771-777, 1991.

6

Frank L. Lewis.
Optimal Estimation.
John Wiley & Sons, Inc., New York, 1986.

7

J.F.G. de Freitas, M. Niranjan, A.H. Gee, and A. Doucet.
Sequential monte carlo methods for optimisation of neural network models.
Technical Report CUES/F-INFENG/TR-328, Dept. of Engineering, University of Cambridge, Nov 1998.

8

Simon J. Julier.
The Scaled Unscented Transformation.
To appear in Automatica, February 2000.

9

A. Dempster, N. M. Laird, and D.B. Rubin.
Maximum-likelihood from incomplete data via the EM algorithm.
Journal of the Royal Statistical Society, B39:1-38, 1977.

10

E. A. Wan and A. T. Nelson.
Neural dual extended Kalman filtering: applications in speech enhancement and monaural blind signal separation.
In Proc. Neural Networks for Signal Processing Workshop. IEEE, 1997.

11

Michael B. Matthews.
A state-space approach to adaptive nonlinear filtering using recurrent neural networks.
In Proceedings IASTED Internat. Symp. Artificial Intelligence Application and Neural Networks, pages 197-200, 1990.

12

R. van der Merwe, J. F. G. de Freitas, A. Doucet, and E. A. Wan.
The Unscented Particle Filter.
Technical report, Dept. of Engineering, University of Cambridge, 2000.
In preparation.

13

Eric A. Wan and Rudolph van der Merwe.
The Unscented Bayes Filter.
Technical report, CSLU, Oregon Graduate Institute of Science and Technology, 2000.
In preparation (http://speech.bme.ogi.edu/nsel).