Large margin mixture of AR models for time series classification

Applied Soft Computing Journal

Volumn 13, Issue 1, 2013, Pages 361-371

  Kini, B Venkataramana ^a   Sekhar, C Chandra ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

Generative and discriminative hybrid models; Large margin autoregressive model; Large margin mixture autoregressive model; Outlier detection; Rejection option; Time series classification

Indexed keywords

AUTO REGRESSIVE MODELS; HYBRID MODEL; OUTLIER DETECTION; REJECTION OPTION; TIME SERIES CLASSIFICATIONS;

IMAGE RETRIEVAL; OPTIMIZATION; SUPPORT VECTOR MACHINES; TIME SERIES;

MIXTURES;

EID: 84869475595     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2012.08.027     Document Type: Article

References (32)

1. G.E.P. Box, G.M. Jenkins, and G.C. Reinsel Time Series Analysis, Forecasting and Control 3rd ed. 1994 Prentice Hall New Jersey
2. V.N. Vapnik Statistical Learning Theory 1998 John Wiley & Sons New York
3. T.W. Liao, F.M. Tang, J. Qu, and P.J. Blau Grinding wheel condition monitoring with boosted minimum distance classifiers Mechanical Systems and Signal Processing 22 2008 217 232
4. T.W. Liao Feature extraction and selection from acoustic emission signals with an application in grinding wheel condition monitoring Engineering Applications of Artificial Intelligence 23 2010 74 84
5. H.A. Guvenir, B. Acar, G. Demiroz, and A. Cekin A supervised learning algorithm for arrhythmia analysis Computers in Cardiology, Sweden 24 1997 433 436
6. M.H. Song, J. Lee, P.C. Sung, J.L. Kyoung, and K.Y. Sun Support vector machine based arrhythmia classification using reduced features International Journal of Control, Automation and Systems 2 2005 571 579
7. M.J.F. Gales Discriminative models for speech recognition Proceedings of the Information Theory and Applications Workshop 2007 170 176
8. O. Yakhnenko, A. Silvescu, and V. Honavar Discriminatively trained Markov model for sequence classification Proceedings of the International Conference on Data Mining 2005 498 505
9. B. Taskar, C. Guestrin, and D. Koller Max-margin Markov networks Proceedings of the Neural Information Processing Systems 2003 25 32
10. F. Sha, and L.K. Saul Large margin hidden Markov models for automatic speech recognition Proceedings of the Neural Information Processing Systems 2006 1249 1256
11. X. He, L. Deng, and W. Chou Discriminative learning in sequential pattern recognition IEEE Signal Processing Magazine 25 2008 14 36
12. A.B. Chan, and N. Vasconcelos Probabilistic kernels for the classification of auto-regressive visual processes IEEE Conference on Computer Vision and Pattern Recognition San Diego 2005 846 851
13. T. Jebara, R. Kondor, A. Howard, K. Bennett, and N. Cesa-bianchi Probability product kernels Journal of Machine Learning Research 5 2004 819 844
14. D. Ge, N. Srinivasan, S.M. Krishnan, Cardiac arrhythmia classification using autoregressive modeling, Biomedical Engineering, OnLine: http://www.biomedical-engineering-online.com/content/1/1/5, 2002.
15. N. Huan, and R. Palaniappan Neural network classification of autoregressive features from electroencephalogram signals for brain computer interface design Journal of Neural Engineering 3 2004 142 150
16. K. Kalpakis, D. Gada, and V. Puttagunta Distance measures for effective clustering of ARIMA time series Proceedings of the IEEE International Conference on Data Mining 2001 273 280
17. B.V. Kini, and C.C. Sekhar Large margin AR model for time series classification International Conference on Pattern Recognition Tampa 2008 1 4
18. L. Rabiner, and B. Juang Fundamentals of Speech Recognition 1993 Prentice Hall Signal Processing Series New Jersey
19. J. Nocedal, and S.J. Wright Numerical Optimization 2nd ed. 2006 Springer-Verlag New York
20. F. Sha, Large Margin Training of Acoustic Models for Speech Recognition, Ph.D. Theis, University of Pennsylvania, 2007.
21. L. Haupt, and S.E. Haupt Practical Genetic Algorithms 1998 John Wiley & Sons
22. F. Sha, and L.K. Saul Large margin Gaussian mixture modeling for phonetic classification and recognition Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing 2006 265 268
23. J. Pan, and W.J. Tompkins A real-time QRS detection algorithm IEEE Transactions on Biomedical Engineering 32 1985 230 236
24. Y. Xiong, and D. Yeung Time series clustering with ARMA mixtures Journal of Pattern Recognition 37 2004 1675 1689
25. C.S. Wong, and W.K. Li On a mixture autoregressive model Journal of the Royal Statistical Society 62 2000 95 115
26. D.A. Coast, R.M. Stren, C.G. Cano, and S.A. Briller An approach to cardiac arrhythmia analysis using hidden Markov models IEEE Transactions on Biomedical Engineering 37 1990 826 836
27. ISOLET Corpus Release 1.1, Center for Spoken Language Understanding 2000 Oregon Graduate Institute Hillsboro
28. S. Katagiri, and C.H. Lee A new HMM/LVQ hybrid algorithm for speech recognition Proceedings of the Global Telecommunications IEEE Conference 1990 1032 1036
29. H. Jiang, X. Li, and C. Liu Large margin hidden Markov models for speech recognition IEEE Transactions on Audio, Speech, and Language Processing 14 2006 1584 1595
30. L. Gu, and K. Rose Substate tying with combined parameter training and reduction in tied-mixture HMM design IEEE Transactions on Audio and Speech Processing 10 2002 137 145
31. C. Hsu, C. Chang, C. Lin, A Practical Guide to Support Vector Classification, Technical Report, Dept. of Computer Science and Information Engineering, National Taiwan University, Taipei, 2003.
32. Z.A. Kerin, and J.I. Aunon A new model for communication between man and his surroundings IEEE Transactions on Biomedical Engineering 37 12 1990 1209 1214