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Non-linear Time Series Analysis:
This section contains papers which discuss various modeling
techniques for a non-linear time series.
- General techniques:
- J. Farmer and J. Sidorowich,
"Predicting chaotic time series,"
Physical Review Letters,
vol. 59, no. 8, pp. 845-848, August 1987
[pdf].
- H. Abarbanel,
"Prediction in chaotic nonlinear systems: Methods
for time series with broadband Fourier spectra,"
Physical Review A, The American Physical
Society,
vol. 41, no. 4, pp. 1782-1807, February 1990
[pdf].
- M. Casdagli,
"Nonlinear Prediction of Chaotic Time Series,"
Physica D. Nonlinear Phenomena,
vol. 35, no. 3, pp. 335-356, May 1989.
- Discriminative techniques:
- S. Mukherjee, E. Osuna, F. Girosi,
"Nonlinear Prediction of Chaotic Time Series using
Support Vector Machines,"
Proceedings of IEEE Workshop on Neural Networks for
Signal Processing VII, NNSP'97,
Amelia Island, Fl, USA, pp. 511-519, 1997.
General Nonlinear Statistics:
This section contains papers which are drawn from the general
mathematics and statistics literature, which discuss the theory
and background of various statistical methods explored in this
project.
- Particle Filtering:
- S. Haykin and E. Moulines,
"From Kalman to Particle Filters,"
IEEE International Conference on Acoustics,
Speech, and Signal Processing,
Philadelphia, Pennsylvania, USA, March 2005
[pdf].
- M.W. Andrews,
"Learning And Inference In Nonlinear State-Space Models,"
Gatsby Unit for Computational Neuroscience,
University College, London, U.K., December 2004 (in
preparation)
[pdf].
- P. Djuric, J. Kotecha, J. Zhang, Y. Huang, T. Ghirmai,
M. Bugallo, and J. Miguez,
"Particle Filtering,"
IEEE Magazine on Signal Processing,
vol. 20, no. 5, pp. 19-38, September 2003.
- N. Arulampalam, S. Maskell, N. Gordan, and T. Clapp,
"Tutorial On Particle Filters For Online Nonlinear/
Non-Gaussian Bayesian Tracking,"
IEEE Transactions on Signal Processing,
vol. 50, no. 2, pp. 174-188, February 2002
[pdf].
- R. van der Merve, N. de Freitas, A. Doucet, and E. Wan,
"The Unscented Particle Filter,"
Technical Report CUED/F-INFENG/TR 380,
Cambridge University Engineering Department,
Cambridge University, U.K., August 2000
[ps.gz].
- Kalman Filtering:
- G. Welch and G. Bishop,
"An Introduction to the Kalman Filter,"
Technical Report TR 95-041,
Department of Computer Science,
University of North Carolina at Chapel Hill,
Chapel Hill, NC, USA, April 2004
[pdf].
- Simon J. Julier, Jeffrey K. Ulhmann, "A New Extension of the Kalman Filter to Nonlinear Systems", Int. Symp. Aerospace/Defense Sensing, Simul. and Controls, Orlando, FL, 1997 [pdf]
Applications to Speech Recognition and Signal Processing:
This section contains papers which are related to applications of
nonlinear statistical methods in speech and signal processing.
- Particle Filtering:
- S. Gannot, and M. Moonen,
"On The Application Of The Unscented Kalman Filter To
Speech Processing,"
International Workshop on Acoustic Echo and Noise,
Kyoto, Japan, pp. 27-30, September 2003
[pdf].
- J.P. Norton, and G.V. Veres,
"Improvement Of The Particle Filter By Better Choice Of
The Predicted Sample Set,"
presented at the 15th IFAC Triennial World Congress,
Barcelona, Spain, July 2002
[pdf].
- J. Vermaak, C. Andrieu, A. Doucet, and S.J. Godsill,
"Particle Methods For Bayesian Modeling And Enhancement
Of Speech Signals,"
IEEE Transaction on Speech and Audio Processing,
vol. 10, no. 3, pp. 173-185, March 2002
[pdf].
State of Art ASR Systems:
This section contains papers which are related to State of Art
Automatic Speech Recognition Systems.
- Discriminative Methods:
- D. Povey, M.J.F. Gales, D.Y. Kim and P.C. Woodland,
"MMI-MAP and MPE-MAP for Acoustic Model Adaption,"
Proceedings of Euroscpeech 2003,
Geneva, Switzerland, pp. 1981-1984, September 2003
[ ps.gz,
pdf].
- D. Povey, P.C. Woodland, and M.J.F. Gales,
"Discriminative map for acoustic model adaption,"
IEEE International Conference on Acoustics,
Speech, and Signal Processing,
Hong-Kong,
vol. 1, pp I-312-315, April 2003
[ ps.gz ].
- D. Povey, and P.C. Woodland,
"Minimum Phone Error and I-Smoothing for Improved
Discriminative Training,"
IEEE International Conference on Acoustics,
Speech, and Signal Processing,
Orlando, Florida, USA, vol. 1, pp. I-105-108, May 2002.
Useful Resources:
This section contains useful external resources such as links to
software, applets, Matlab links etc.
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