M. Fréchet, Sur quelques points du calcul fonctionnel, Thèse, Faculté des sciences de Paris, 1906.
DOI : 10.1007/BF03018603

V. M. Velichko and N. G. Zagoruyko, Automatic recognition of 200 words, International Journal of Man-Machine Studies, vol.2, issue.3, pp.223-234, 1970.
DOI : 10.1016/S0020-7373(70)80008-6

H. Sakoe and S. Chiba, A dynamic programming approach to continuous speech recognition, Proceedings of the 7th International Congress of Acoustic, pp.65-68, 1971.

L. Chen and R. Ng, On The Marriage of Lp-norms and Edit Distance, Proceedings of the Thirtieth International Conference on Very Large Data Bases - ser. VLDB '04. VLDB Endowment, pp.792-803, 2004.
DOI : 10.1016/B978-012088469-8.50070-X

P. Marteau, Time warp edit distance with stiffness adjustment for time series matching Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.31, issue.2, pp.306-318, 2009.

K. H. Fasman and S. S. , An introduction to biological sequence analysis, Computational Methods in Molecular Biology, pp.21-42, 1998.
DOI : 10.1016/S0167-7306(08)60460-3

L. Wang and T. Jiang, On the Complexity of Multiple Sequence Alignment, Journal of Computational Biology, vol.1, issue.4, pp.337-348, 1994.
DOI : 10.1089/cmb.1994.1.337

W. Just and W. Just, Computational Complexity of Multiple Sequence Alignment with SP-Score, Journal of Computational Biology, vol.8, issue.6, pp.615-623, 1999.
DOI : 10.1089/106652701753307511

H. Carrillo and D. Lipman, The Multiple Sequence Alignment Problem in Biology, SIAM Journal on Applied Mathematics, vol.48, issue.5, pp.1073-1082, 1988.
DOI : 10.1137/0148063

L. Gupta, D. Molfese, R. Tammana, and P. Simos, Nonlinear alignment and averaging for estimating the evoked potential, IEEE Transactions on Biomedical Engineering, vol.43, issue.4, pp.348-356, 1996.
DOI : 10.1109/10.486255

V. Niennattrakul and C. Ratanamahatana, Shape averaging under Time Warping, 2009 6th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, pp.626-629, 2009.
DOI : 10.1109/ECTICON.2009.5137128

W. Abdulla, D. Chow, and G. Sin, Cross-words reference template for dtw-based speech recognition systems, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region, pp.1576-1579, 2003.
DOI : 10.1109/TENCON.2003.1273186

V. Hautamaki, P. Nykanen, and P. Franti, Time-series clustering by approximate prototypes, 2008 19th International Conference on Pattern Recognition, pp.1-4, 2008.
DOI : 10.1109/ICPR.2008.4761105

F. Petitjean, A. Ketterlin, and P. Gançarski, A global averaging method for dynamic time warping, with applications to clustering, Pattern Recognition, vol.44, issue.3, pp.678-693, 2011.
DOI : 10.1016/j.patcog.2010.09.013

F. Petitjean and P. Gançarski, Summarizing a set of time series by averaging: From Steiner sequence to compact multiple alignment, Theoretical Computer Science, vol.414, issue.1, pp.76-91, 2012.
DOI : 10.1016/j.tcs.2011.09.029

S. Soheily-khal, A. Douzal-chouakria, and E. Gaussier, Time series centroid estimation under weighted and kernel dynamic time warping, p.2014

H. Shimodaira, K. I. Noma, M. Nakai, and S. Sagayama, Dynamic Time-Alignment Kernel in Support Vector Machine, Advances in Neural Information Processing Systems 14, 2002.

V. Niennattrakul and C. Ratanamahatana, Inaccuracies of shape averaging method using dynamic time warping for time series data, " in Computational Science ? ICCS 2007, ser. Lecture Notes in Computer Science, pp.513-520, 2007.

P. Marteau and S. Gibet, On Recursive Edit Distance Kernels With Application to Time Series Classification, IEEE Transactions on Neural Networks and Learning Systems, vol.26, issue.6, pp.1-14, 2014.
DOI : 10.1109/TNNLS.2014.2333876
URL : https://hal.archives-ouvertes.fr/hal-00486916

M. Cuturi, J. Vert, O. Birkenes, and T. Matsui, A Kernel for Time Series Based on Global Alignments, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, pp.413-416, 2007.
DOI : 10.1109/ICASSP.2007.366260

N. Aronszajn, Theory of reproducing kernels, Transactions of the American Mathematical Society, vol.68, issue.3, 1950.
DOI : 10.1090/S0002-9947-1950-0051437-7

B. Schölkopfsch¨schölkopf, R. Herbrich, and A. J. Smola, A generalized representer theorem, Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory, ser. COLT '01/EuroCOLT '01

M. J. Powell, The bobyqa algorithm for bound constrained optimization without derivatives, 2009.

E. J. Keogh, X. Xi, L. Wei, C. Ratanamahatana, F. Petitjean et al., The UCR time series classification-clustering datasets http://wwwcs.ucr.edu/ eamonn/time series data Dynamic time warping averaging of time series allows faster and more accurate classification, Proceedings of the 14th IEEE International Conference on Data Mining, pp.470-479, 2006.

M. Lichman and P. Marteau, Uci machine learning repository Available: http://archive Pulse width modulation data sets, 2007.

J. Dem?ar, Statistical comparisons of classifiers over multiple data sets, J. Mach. Learn. Res, vol.7, pp.1-30, 2006.

M. Hollander and D. Wolfe, Nonparametric Statistical Methods, ser Wiley Series in Probability and Statistics Available: https://books.google.fr/books?id=RJAQAQAAIAAJ [30] T. Galili, " R code for the friedman test post hoc analysis, 1999.