Kernel sparse representation for time series classification

Information Sciences

Volumn 292, Issue , 2015, Pages 15-26

  Chen, Zhihua ^a   Zuo, Wangmeng ^a   Hu, Qinghua ^b   Lin, Liang ^c  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b TIANJIN UNIVERSITY   (China)

^c SUN YAT SEN UNIVERSITY   (China)

Author keywords

Dictionary learning; Kernel method; Sparse representation; Time series classification

Indexed keywords

COMPUTATIONAL EFFICIENCY; TIME SERIES;

CLASSIFICATION ACCURACY; CLASSIFICATION PERFORMANCE; DICTIONARY LEARNING; KERNEL METHODS; LINEAR COMBINATIONS; NEAREST NEIGHBOR CLASSIFICATION; SPARSE REPRESENTATION; TIME SERIES CLASSIFICATIONS;

C (PROGRAMMING LANGUAGE);

EID: 84922602038     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.08.066     Document Type: Article

References (54)

1. M. Aharon, M. Elad, and A. Bruckstein K-SVD: an algorithm for designing of overcomplete dictionaries for sparse representation IEEE Trans. Signal Process. 54 11 2006 4311 4322
2. F.I. Bashir, A.A. Khokhar, and D. Schonfeld Object trajectory-based activity classification and recognition using hidden Markov models IEEE Trans. Image Process. 16 7 2007 1912 1919
3. D.J. Berndt, J. Clifford, Using dynamic time warping to find patterns in time series, AAAI-94 Workshop on Knowledge Discovery in Databases, 1994, pp. 229-248.
4. E. Candès, J. Romberg, and T. Tao Stable signal recovery from incomplete and inaccurate measurements Commun. Pure Appl. Math. 59 8 2006 1207 1223
5. E. Candès, and T. Tao Decoding by linear programming IEEE Trans. Inform. Theory 51 12 2005 4203 4215
6. L. Chen, R. Ng, On the marriage of Lp-norms and edit distance, in: Proceedings of the Thirtieth International Conference on Very Large Data Bases (VLDB'04), 2004, pp. 792-803.
7. L. Chen, M.T. Özsu,V. Oria, Robust and fast similarity search for moving object trajectories, in: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data (SIGMOD'05), 2005, pp. 491-502.
8. Y.H. Chen, E.K. Garcia, M.R. Gupta, A. Rahimi, and L. Cazzanti Similarity-based classification: concepts and algorithms J. Machine Learn. Res. 10 2009 747 776
9. H. Deng, G. Runger, E. Tuv, and M. Vladimir A time series forest for classification and feature extraction Inform. Sci. 239 2013 142 153
10. D.L. Donoho Compressed sensing IEEE Trans. Inform. Theory 52 4 2006 1289 1306
11. R.O. Duta, P.E. Hart, and D.G. Stork Pattern Classification second ed. 2000 John Wiley & Sons New York
12. K. Engan, S.O. Aase, and J.H. Husøy Multi-frame compression: theory and design EURASIP Signal Process. 80 10 2000 2121 2140
13. T.C. Fu, C.W. Law, K.K. Chan, F.L. Chung, C.M. Ng, Stock time series categorization and clustering via SB-tree optimization, in: Proceedings of the Third International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'06), 2006, pp. 1130-1139.
14. S. Gao, I.W.-H. Tsang, and Y. Ma Learning category-specific dictionary and shared dictionary for fine-grained image categorization IEEE Trans. Image Process. 23 2 2014 623 634
15. S. Gao, I.W. Tsang, and L.T. Chia Sparse representation with kernels IEEE Trans. Image Process. 22 2 2013 423 434
16. S. Gudmundsson, T.P. Runarsson, S. Sigurdsson, Support vector machines and dynamic time warping for time series, in: IEEE International Joint Conference on Neural Networks (IJCNN'08), 2008, pp. 2772-2776.
17. A. Jalalian, and S.K. Chalup GDTW-P-SVMs: variable-length time series analysis using support vector machines Neurocomputing 99 1 2013 270 282
18. K. Jia, T.H. Chan, Y. Ma, Robust and practical face recognition via structured sparsity, in: Proceedings of the 12th European Conference on Computer Vision (ECCV'12), 2012, pp. 331-344.
19. Z.L. Jiang, Z. Lin, L.S. Davis, Learning a discriminative dictionary for sparse coding via label consistent K-SVD, in: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR'11), 2011, pp. 1697-1704.
20. Z. Jiang, Z. Lin, and L.S. Davis Label consistent K-SVD: learning adiscriminative dictionary for recognition IEEE Trans. Pattern Anal. Machine Intell. 2013
21. E. Keogh, and C.A. Ratanamahatana Exact indexing of dynamic time warping Knowl. Inform. Syst. 7 3 2005 358 386
22. E. Keogh, and S. Kasetty On the need for time series data mining benchmarks: a survey and empirical demonstration Data Mining Knowl. Discovery 7 4 2003 349 371
23. E. Keogh, Q. Zhu, B. Hu, Y. Hao, X. Xi, L. Wei, C.A. Ratanamahatana, The UCR Time Series Classification/Clustering, 2011. < www.cs.ucr.edu/∼eamonn/time-series-data/ >.
24. M. Krawczak, and G. Szkatuła An approach to dimensionality reduction in time series Inform. Sci. 260 2014 15 36
25. K. Kreutz-Delgado, J.F. Murray, B.D. Rao, K. Engan, T.W. Lee, and T.J. Sejnowski Dictionary learning algorithms for sparse representation Neural Comput. 15 2 2003 349 396
26. H.S. Lei, B.Y. Sun, A study on the dynamic time warping in kernel machines, in: Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (SITIS '07), 2007, pp. 839-845.
27. J.F. Lichtenauer, E.A. Hendriks, and M.J.T. Reinders Sign language recognition by combining statistical DTW and independent classification IEEE Trans. Pattern Anal. Machine Intell. 30 11 2008 2040 2046
28. L. Lin, X. Liu, and S.-C. Zhu Layered graph matching with composite cluster sampling IEEE Trans. Pattern Anal. Machine Intell. 32 8 2010 1426 1442
29. H. Liu, Y. Liu, and F. Sun Traffic sign recognition using group sparse coding Inform. Sci. 266 2014 75 89
30. E.A. Maharaj, and P. D'Urso Fuzzy clustering of time series in the frequency domain Inform. Sci. 181 7 2011 1187 1211
31. J. Mairal, F. Bach, and J. Ponce Task-driven dictionary learning IEEE Trans. Pattern Anal. Machine Intell. 34 4 2012 791 804
32. J. Mairal, F. Bach, J. Ponce, G. Sapiro, and A. Zisserman Supervised dictionary learning Adv. Neural Inform. Process. Syst. 2008
33. V. Mäkinen, Using edit distance in point-pattern matching, in: Proc. 8th International Symposium on String Processing and Information Retrieval (SPIRE'01), 2001, pp. 153-161.
34. P.F. Marteau Time warp edit distance with stiffness adjustment for time series matching IEEE Trans. Pattern Anal. Machine Intell. 31 2 2009 306 318
35. H.V. Nguyen, V.M. Patel, N.M. Nasrabadi, R. Chellappa, Kernel dictionary learning, in: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'12), 2012, pp. 2021-2024.
36. H. Van Nguyen, V.M. Patel, N.M. Nasrabadi, and R. Chellappa Design of non-linear kernel dictionaries for object recognition IEEE Trans. Image Process. 22 12 2013 5123 5135
37. K. Noponen, J. Kortelainen, and T. Seppänen Invariant trajectory classification of dynamical systems with a case study on ECG Pattern Recogn. 42 9 2009 1832 1844
38. H. Pree, B. Herwig, T. Gruber, B. Sick, K. David, and P. Lukowicz On general purpose time series similarity measures and their use as kernel functions in support vector machines Inform. Sci. 281 2014 478 495
39. M. Pulido, P. Melin, and O. Castillo Particle swarm optimization of ensemble neural networks with fuzzy aggregation for time series prediction of the Mexican Stock Exchange Inform. Sci. 280 2014 188 204
40. M. Vlachos, M. Hadjieleftheriou, D. Gunopulos, E. Keogh, Indexing multi-dimensional time-series with support for multiple distance measures, in: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'03), 2003, pp. 216-225.
41. X.Y. Wang, A. Mueen, H. Ding, G. Trajcevski, P. Scheuermann, and E. Keogh Experimental comparison of representation methods and distance measures for time series data Data Mining Knowl. Discovery 26 2013 275 309
42. J. Wright, A. Yang, A. Ganesh, S. Sastry, and Y. Ma Robust face recognition via sparse representation IEEE Trans. Pattern Anal. Machine Intell. 31 2 2009 210 227
43. Y. Xu, Q. Zhu, Z. Fan, D. Zhang, J. Mi, and Z. Lai Using the idea of the sparse representation to perform coarse-to-fine face recognition Inform. Sci. 238 2013 138 148
44. A.Y. Yang, Z.H. Zhou, A.G. Balasubramanian, S. Sastry, and Y. Ma Fast l1-minimization algorithms for robust face recognition IEEE Trans. Image Process. 22 8 2013 3234 3246
45. M. Yang, L. Zhang, X. Feng, D. Zhang, Fisher discrimination dictionary learning for sparse representation, in: 2011 IEEE International Conference on Computer Vision (ICCV'11), 2011, pp. 543-550.
46. S. Yang, Y. Lv, Y. Ren, L. Yang, and L. Jiao Unsupervised images segmentation via incremental dictionary learning based sparse representation Inform. Sci. 269 2014 48 59
47. J. Yin, Z.H. Liu, Z. Jin, and W.K. Yang Kernel sparse representation based classification Neurocomputing 77 1 2012 120 128
48. D. Yu, X. Yu, Q. Hu, J. Liu, and A. Wu Dynamic time warping constraint learning for large margin nearest neighbor Inform. Sci. 181 13 2011 2787 2796
49. B. Zhang, F. Karray, Q. Li, and L. Zhang Sparse representation classifier for microaneurysm detection and retinal blood vessel extraction Inform. Sci. 200 2012 78 90
50. D. Zhang, W.M. Zuo, D. Zhang, H.Z. Zhang, Time series classification using support vector machine with Gaussian elastic metric kernel, in: Proceedings of 20th International Conference on Pattern Recognition (ICPR'10), 2010, pp. 29-32.
51. H.C. Zhang, N.M. Nasrabadi, Y.N. Zhang, and T.S. Huang Joint dynamic sparse representation for multi-view face recognition Pattern Recogn. 45 4 2012 1290 1298
52. L. Zhang, M. Yang, X. Feng, Sparse representation or collaborative representation: which helps face recognition, in: 2011 IEEE International Conference on Computer Vision (ICCV'11), 2011, pp. 471-478.
53. L. Zhang, W.D. Zhou, P.C. Chang, J. Liu, Z. Yan, T. Wang, and F.Z. Li Kernel sparse representation-based classifier IEEE Trans. Signal Process. 60 4 2012 1684 1695
54. Q. Zhang, B.X. Li, Discriminative K-SVD for dictionary learning in face recognition, in: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR'10), 2010, pp. 2691-2698.