-
1
-
-
0014738902
-
On state estimation in switching environments
-
Jan.
-
G.A. Ackerson and K.S. Fu, "On state estimation in switching environments," IEEE Trans. Automat. Contr., vol. AC-15, pp. 10-17, Jan. 1970.
-
(1970)
IEEE Trans. Automat. Contr.
, vol.AC-15
, pp. 10-17
-
-
Ackerson, G.A.1
Fu, K.S.2
-
2
-
-
0001588636
-
Smooth on-line learning algorithms for hidden Markov models
-
P. Baldi and Y. Chauvin, "Smooth on-line learning algorithms for hidden Markov models," Neural Comput., vol. 6, pp. 305-316, 1994.
-
(1994)
Neural Comput.
, vol.6
, pp. 305-316
-
-
Baldi, P.1
Chauvin, Y.2
-
3
-
-
0002629256
-
Bidirectional dynamics for protein secondary structure prediction
-
R. Sun and C.L. Giles, Eds. New York: Springer-Verlag
-
P. Baldi, S. Brunak, P. Frasconi, G. Pollastri, and G. Soda, "Bidirectional dynamics for protein secondary structure prediction," in Sequence Learning: Paradigms, Algorithms, and Applications, R. Sun and C.L. Giles, Eds. New York: Springer-Verlag, 2001, pp. 80-104.
-
(2001)
Sequence Learning: Paradigms, Algorithms, and Applications
, pp. 80-104
-
-
Baldi, P.1
Brunak, S.2
Frasconi, P.3
Pollastri, G.4
Soda, G.5
-
5
-
-
0030242097
-
Input/output HMMs for sequence processing
-
Sept.
-
Y. Bengio and P. Frasconi, "Input/output HMMs for sequence processing," IEEE Trans. Neural Networks, vol. 7, pp. 1231-1249, Sept. 1996.
-
(1996)
IEEE Trans. Neural Networks
, vol.7
, pp. 1231-1249
-
-
Bengio, Y.1
Frasconi, P.2
-
6
-
-
0000802938
-
Markovian models for sequential data
-
Y. Bengio, "Markovian models for sequential data," Neural Comp. Surveys, vol. 2, pp. 129-162, 1998.
-
(1998)
Neural Comp. Surveys
, vol.2
, pp. 129-162
-
-
Bengio, Y.1
-
8
-
-
85153959666
-
Convergence properties of the k-means algorithms
-
G. Tesauro et al., Eds. Cambridge, MA: MIT Press
-
L. Bottou and Y. Bengio et al., "Convergence properties of the k-means algorithms," in Advantages in Neural Information Processing Systems 7, G. Tesauro et al., Eds. Cambridge, MA: MIT Press, 1995, pp. 585-592.
-
(1995)
Advantages in Neural Information Processing Systems
, vol.7
, pp. 585-592
-
-
Bottou, L.1
Bengio, Y.2
-
9
-
-
84878986189
-
Approximate learning of dynamic models
-
Denver, CO
-
X. Boyen and D. Koller, "Approximate learning of dynamic models," in Proc. 12th Annu. Conf. Neural Inform. Processing Syst., Denver, CO, 1998, pp. 396-402.
-
(1998)
Proc. 12th Annu. Conf. Neural Inform. Processing Syst.
, pp. 396-402
-
-
Boyen, X.1
Koller, D.2
-
10
-
-
0001119510
-
Mixtures of controllers for jump linear and nonlinear plants
-
J.D. Cowen, G. Tesauro, and J. Alspector, Eds. San Mateo, CA: Morgan Kaufmann
-
T.W. Cacciatore and S.J. Nowlan, "Mixtures of controllers for jump linear and nonlinear plants," in Advances in Neural Information Processing Systems 6, J.D. Cowen, G. Tesauro, and J. Alspector, Eds. San Mateo, CA: Morgan Kaufmann, 1994, pp. 719-726.
-
(1994)
Advances in Neural Information Processing Systems
, vol.6
, pp. 719-726
-
-
Cacciatore, T.W.1
Nowlan, S.J.2
-
11
-
-
0029342027
-
A necessary condition for effective performance of the multiple model adaptive estimator
-
Sept.
-
M.J. Caputi, "A necessary condition for effective performance of the multiple model adaptive estimator," IEEE Trans. Aerosp. Electron. Syst., vol. 31, pp. 1132-1138, Sept. 1995.
-
(1995)
IEEE Trans. Aerosp. Electron. Syst.
, vol.31
, pp. 1132-1138
-
-
Caputi, M.J.1
-
12
-
-
0000193853
-
On Gibbs sampling for state space models
-
C.K. Carter and R. Kohn, "On Gibbs sampling for state space models," Biometrika, vol. 81, pp. 541-553, 1994.
-
(1994)
Biometrika
, vol.81
, pp. 541-553
-
-
Carter, C.K.1
Kohn, R.2
-
13
-
-
0002596525
-
A comparison of the forecast performance of Markov-switching and threshold autoregressive models of U.S. GNP
-
M.P. Clements and H.M. Krolzig, "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of U.S. GNP," Econom. J., vol. 1, pp. 47-75, 1998.
-
(1998)
Econom. J.
, vol.1
, pp. 47-75
-
-
Clements, M.P.1
Krolzig, H.M.2
-
14
-
-
0002629270
-
Maximum likelihood from incomplete data via the EM algorithm
-
A.P. Dempster, N.M. Laird, and D.B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Royal Statist. Soc. B., vol. 39, pp. 1-38, 1977.
-
(1977)
J. Royal Statist. Soc. B.
, vol.39
, pp. 1-38
-
-
Dempster, A.P.1
Laird, N.M.2
Rubin, D.B.3
-
15
-
-
0026854213
-
A generalized hidden Markov model with state-conditioned trend functions of time for the speech signal
-
L. Deng, "A generalized hidden Markov model with state-conditioned trend functions of time for the speech signal," Signal Processing, vol. 27, pp. 65-78, 1992.
-
(1992)
Signal Processing
, vol.27
, pp. 65-78
-
-
Deng, L.1
-
16
-
-
0026821564
-
Modeling acoustic transitions in speech by state interpolation HMM
-
Feb.
-
L. Deng, P. Kenny, M. Lennig, and P. Mermelstein, "Modeling acoustic transitions in speech by state interpolation HMM," IEEE Trans. Signal Processing, vol. 40, pp. 265-271, Feb. 1992.
-
(1992)
IEEE Trans. Signal Processing
, vol.40
, pp. 265-271
-
-
Deng, L.1
Kenny, P.2
Lennig, M.3
Mermelstein, P.4
-
18
-
-
0028721469
-
The filtering problem for continuous-time linear systems with Markovian switching coefficients
-
F. Dufour and P. Bertrand, "The filtering problem for continuous-time linear systems with Markovian switching coefficients," Syst. Contr. Lett., vol. 23, pp. 453-461, 1994.
-
(1994)
Syst. Contr. Lett.
, vol.23
, pp. 453-461
-
-
Dufour, F.1
Bertrand, P.2
-
19
-
-
0011849609
-
Stabilizing control for hybrid models
-
Dec.
-
_, "Stabilizing control for hybrid models," IEEE Trans. Automat. Contr., vol. 39, pp. 2354-2357, Dec. 1993.
-
(1993)
IEEE Trans. Automat. Contr.
, vol.39
, pp. 2354-2357
-
-
-
22
-
-
0001646121
-
Variational learning for switching state-space models
-
Z. Ghahramani and G.E. Hinton, "Variational learning for switching state-space models," Neural Comput., vol. 12, pp. 963-996, 1998.
-
(1998)
Neural Comput.
, vol.12
, pp. 963-996
-
-
Ghahramani, Z.1
Hinton, G.E.2
-
23
-
-
0002049440
-
Learning dynamic Bayesian networks
-
Adaptive Processing of Sequences and Data Structures, C.L. Giles and M. Gori, Eds. New York: Springer-Verlag
-
Z. Ghahramani, "Learning dynamic Bayesian networks," in Adaptive Processing of Sequences and Data Structures, C.L. Giles and M. Gori, Eds. New York: Springer-Verlag, 1998, Lecture Notes in Artificial Intelligence, pp. 168-197.
-
(1998)
Lecture Notes in Artificial Intelligence
, pp. 168-197
-
-
Ghahramani, Z.1
-
24
-
-
84899008192
-
Learning nonlinear dynamical systems using an EM algorithm
-
M.S. Kearns, S.A. Solla, and D.A. Cohn, Eds. Cambridge, MA: MIT Press
-
Z. Ghahramani and S. Roweis, "Learning nonlinear dynamical systems using an EM algorithm," in Advances in Neural Information Processing Systems 11, M.S. Kearns, S.A. Solla, and D.A. Cohn, Eds. Cambridge, MA: MIT Press, 1999, pp. 599-605.
-
(1999)
Advances in Neural Information Processing Systems
, vol.11
, pp. 599-605
-
-
Ghahramani, Z.1
Roweis, S.2
-
25
-
-
45149138487
-
Analysis of times series subject to changes in regime
-
J.D. Hamilton, "Analysis of times series subject to changes in regime," J. Econom., vol. 45, pp. 39-70, 1990.
-
(1990)
J. Econom.
, vol.45
, pp. 39-70
-
-
Hamilton, J.D.1
-
26
-
-
0003410290
-
-
Princeton, NJ: Princeton Univ. Press
-
_, Time Series Analysis. Princeton, NJ: Princeton Univ. Press, 1994.
-
(1994)
Time Series Analysis
-
-
-
27
-
-
0001940458
-
Adaptive mixtures of local experts
-
R.A. Jacobs, M.I. Jordan, S.J. Nowlan, and G.E. Hinton, "Adaptive mixtures of local experts," Neural Comput., vol. 3, pp. 79-87, 1991.
-
(1991)
Neural Comput.
, vol.3
, pp. 79-87
-
-
Jacobs, R.A.1
Jordan, M.I.2
Nowlan, S.J.3
Hinton, G.E.4
-
28
-
-
0029247140
-
Identification of nonlinear system structure and parameters using regime decomposition
-
T.A. Johansen and B.A. Foss, "Identification of nonlinear system structure and parameters using regime decomposition," Automatica, vol. 31, pp. 321-326, 1995.
-
(1995)
Automatica
, vol.31
, pp. 321-326
-
-
Johansen, T.A.1
Foss, B.A.2
-
29
-
-
0000262562
-
Hierarchical mixtures of experts and the EM algorithm
-
M.I. Jordan and R.A. Jacobs, "Hierarchical mixtures of experts and the EM algorithm," Neural Comput., vol. 6, pp. 181-214, 1994.
-
(1994)
Neural Comput.
, vol.6
, pp. 181-214
-
-
Jordan, M.I.1
Jacobs, R.A.2
-
30
-
-
0022097649
-
Maximum-likelihood estimation for mixture multivariate stochastic observations of Markov chains
-
B.H. Juang, "Maximum-likelihood estimation for mixture multivariate stochastic observations of Markov chains," AT & T Tech. J., vol. 64, 1985.
-
(1985)
AT & T Tech. J.
, vol.64
-
-
Juang, B.H.1
-
31
-
-
0031034197
-
Predictive modular neural networks for time series classification
-
A. Kehagias and V. Petridis, "Predictive modular neural networks for time series classification," Neural Networks, vol. 10, pp. 31-49, 1996.
-
(1996)
Neural Networks
, vol.10
, pp. 31-49
-
-
Kehagias, A.1
Petridis, V.2
-
32
-
-
0001481001
-
Time series segmentation using predictive modular neural networks
-
_, "Time series segmentation using predictive modular neural networks," Neural Comput., vol. 9, pp. 1691-1710, 1997.
-
(1997)
Neural Comput.
, vol.9
, pp. 1691-1710
-
-
-
33
-
-
0025388113
-
A linear predictive HMM for vector-valued observations with applications to speech recognition
-
Mar.
-
P. Kenny, M. Lennig, and P. Mermelstein, "A linear predictive HMM for vector-valued observations with applications to speech recognition," IEEE Trans. Acoust., Speech, Signal Processing, vol. 8, pp. 220-225, Mar. 1990.
-
(1990)
IEEE Trans. Acoust., Speech, Signal Processing
, vol.8
, pp. 220-225
-
-
Kenny, P.1
Lennig, M.2
Mermelstein, P.3
-
34
-
-
0034220601
-
Identification of nonstationary dynamics in physiological recordings
-
J. Kohlmorgen, K.R. Mueller, J. Rittweger, and K. Pawelzik, "Identification of nonstationary dynamics in physiological recordings," Biol. Cybern., vol. 83, pp. 73-84, 2000.
-
(2000)
Biol. Cybern.
, vol.83
, pp. 73-84
-
-
Kohlmorgen, J.1
Mueller, K.R.2
Rittweger, J.3
Pawelzik, K.4
-
35
-
-
0028181441
-
Hidden Markov models in computational biology: Applications to protein modeling
-
A. Krogh et al., "Hidden Markov models in computational biology: Applications to protein modeling," J. Mol. Biol., vol. 235, pp. 1501-1531, 1994.
-
(1994)
J. Mol. Biol.
, vol.235
, pp. 1501-1531
-
-
Krogh, A.1
-
38
-
-
0002861635
-
Optimal estimation in the presence of unknown parameters
-
Feb.
-
C.G. Hilborn and D.G. Lainiotis, "Optimal estimation in the presence of unknown parameters," IEEE Trans. Syst. Sci. Cybern., vol. SMC-5, pp. 38-43, Feb. 1969.
-
(1969)
IEEE Trans. Syst. Sci. Cybern.
, vol.SMC-5
, pp. 38-43
-
-
Hilborn, C.G.1
Lainiotis, D.G.2
-
39
-
-
0015039116
-
Optimal adaptive estimation: Structure and parameter adaptation
-
Jan.
-
D.G. Lainiotis, "Optimal adaptive estimation: Structure and parameter adaptation," IEEE Trans. Automat Contr., vol. AC-16, pp. 160-170, Jan. 1971.
-
(1971)
IEEE Trans. Automat Contr.
, vol.AC-16
, pp. 160-170
-
-
Lainiotis, D.G.1
-
41
-
-
0029325388
-
Adaptation and learning using multiple models, switching and tuning
-
Jan.
-
K. Narendra, "Adaptation and learning using multiple models, switching and tuning," IEEE Contr. Syst. Mag., pp. 37-51, Jan. 1995.
-
(1995)
IEEE Contr. Syst. Mag.
, pp. 37-51
-
-
Narendra, K.1
-
43
-
-
0002788893
-
A new view of the EM algorithm that justifies incremental, sparse and other variants
-
M.I. Jordan, Ed. Boston, MA: Kluwer
-
R.M. Neal and G. Hinton, "A new view of the EM algorithm that justifies incremental, sparse and other variants," in Learning in Graphical Models, M.I. Jordan, Ed. Boston, MA: Kluwer, 1998, pp. 355-368.
-
(1998)
Learning in Graphical Models
, pp. 355-368
-
-
Neal, R.M.1
Hinton, G.2
-
44
-
-
0030245363
-
From HMMs to segment models: A unified view of stochastic modeling for speech recognition
-
Mar.
-
M. Ostendorf, V. Digalakis, and O. Kimball, "From HMMs to segment models: A unified view of stochastic modeling for speech recognition," IEEE Trans. Speech Audio Processing, pp. 360-378, Mar. 1996.
-
(1996)
IEEE Trans. Speech Audio Processing
, pp. 360-378
-
-
Ostendorf, M.1
Digalakis, V.2
Kimball, O.3
-
45
-
-
0001558731
-
Annealed competition of experts for a segmentation and classification of switching dynamics
-
K. Pawelzik, J. Kohlmorgen, and K.R. Muller, "Annealed competition of experts for a segmentation and classification of switching dynamics," Neural Comput., vol. 8, pp. 357-372, 1996.
-
(1996)
Neural Comput.
, vol.8
, pp. 357-372
-
-
Pawelzik, K.1
Kohlmorgen, J.2
Muller, K.R.3
-
46
-
-
0000458484
-
A recurrent network implementation of time series classification
-
V. Petridis and A. Kehagias, "A recurrent network implementation of time series classification," Neural Comput., vol. 8, pp. 357-372, 1996.
-
(1996)
Neural Comput.
, vol.8
, pp. 357-372
-
-
Petridis, V.1
Kehagias, A.2
-
47
-
-
0029771135
-
Modular neural networks for MAP classification of time series and the partition algorithm
-
Jan.
-
_, "Modular neural networks for MAP classification of time series and the partition algorithm," IEEE Trans. Neural Networks, vol. 7, pp. 73-86, Jan. 1996.
-
(1996)
IEEE Trans. Neural Networks
, vol.7
, pp. 73-86
-
-
-
49
-
-
0024610919
-
A tutorial on hidden Markov models and selected applications in speech recognition
-
Feb.
-
L.R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. IEEE, vol. 77, pp. 257-285, Feb. 1989.
-
(1989)
Proc. IEEE
, vol.77
, pp. 257-285
-
-
Rabiner, L.R.1
-
50
-
-
0000147488
-
OnLine model selection based on the variational Bayes
-
M. Sato, "OnLine model selection based on the variational Bayes," Neural Comput., vol. 13, pp. 1649-1681, 2001.
-
(2001)
Neural Comput.
, vol.13
, pp. 1649-1681
-
-
Sato, M.1
-
51
-
-
0034850596
-
Topology free hidden Markov models: Application to background modeling
-
B. Stenger et al., "Topology free hidden Markov models: Application to background modeling," in Proc. 8th IEEE Int. Conf. Comput. Vision, vol. I, 2001, pp. 294-301.
-
(2001)
Proc. 8th IEEE Int. Conf. Comput. Vision
, vol.1
, pp. 294-301
-
-
Stenger, B.1
-
53
-
-
0032354661
-
Testing and modeling multivariate threshold models
-
R.S. Tsay, "Testing and modeling multivariate threshold models," J. Amer. Statist. Assoc., vol. 93, pp. 1188-1202, 1998.
-
(1998)
J. Amer. Statist. Assoc.
, vol.93
, pp. 1188-1202
-
-
Tsay, R.S.1
-
54
-
-
0034264299
-
SMEM algorithm for mixture models
-
N. Ueda, R. Nakano, Z. Ghahramani, and G.E. Hinton, "SMEM algorithm for mixture models," Neural Comput., vol. 12, pp. 2109-2128, 2000.
-
(2000)
Neural Comput.
, vol.12
, pp. 2109-2128
-
-
Ueda, N.1
Nakano, R.2
Ghahramani, Z.3
Hinton, G.E.4
-
55
-
-
85045980281
-
Smooth transition autoregressive models-A survey of recent developments
-
D. van Dijk, T. Terasvirta, and P.H. Franses, "Smooth transition autoregressive models-A survey of recent developments,", Econometric Rev., vol. 21, pp. 1-47, 2002.
-
(2002)
Econometric Rev.
, vol.21
, pp. 1-47
-
-
Van Dijk, D.1
Terasvirta, T.2
Franses, P.H.3
-
57
-
-
0003188086
-
Predicting daily probability distributions of S & P500 returns
-
A. Weigend and S. Shi, "Predicting daily probability distributions of S & P500 returns." J. Forecasting, vol. 19, pp. 375-392, 1998.
-
(1998)
J. Forecasting
, vol.19
, pp. 375-392
-
-
Weigend, A.1
Shi, S.2
-
58
-
-
0344073962
-
RBF nets, mixture experts, and Bayesian Ying-Yang learning
-
L. Xu, "RBF nets, mixture experts, and Bayesian Ying-Yang learning," Neurocomput., vol. 19, pp. 223-257, 1998.
-
(1998)
Neurocomput.
, vol.19
, pp. 223-257
-
-
Xu, L.1
-
59
-
-
0033716741
-
Temporal BYY learning for state space approach, hidden Markov model, and blind source separation
-
Nov.
-
_, "Temporal BYY learning for state space approach, hidden Markov model, and blind source separation," IEEE Trans. Signal Processing, vol. 48, pp. 2132-2144, Nov. 2000.
-
(2000)
IEEE Trans. Signal Processing
, vol.48
, pp. 2132-2144
-
-
-
60
-
-
0033308417
-
Reconstruction of chaotic dynamics and robustness to noise with on-line EM algorithm
-
W. Yoshida, S. Ishii, and M. Sato, "Reconstruction of chaotic dynamics and robustness to noise with on-line EM algorithm," presented at the IEEE SMC Conference, 1999.
-
(1999)
IEEE SMC Conference
-
-
Yoshida, W.1
Ishii, S.2
Sato, M.3
|