A. Antoulas, Frequency domain representation and singular value decomposition, 2002.

J. S. Armstrong and J. G. Andress, Exploratory Analysis of Marketing Data: Trees vs. Regression, Journal of Marketing Research, vol.7, issue.4, pp.487-492, 1970.
DOI : 10.2307/3149642

A. Arnéodo, J. Muzy, and D. Sornette, ???Direct??? causal cascade in the stock market, The European Physical Journal B, vol.2, issue.2, pp.277-282, 1998.
DOI : 10.1007/s100510050250

Y. Benjamini and Y. Hochberg, Controlling the false discovery rate: A practical and powerful approach to multiple testing, Journal of the Royal Statistical Society. Series B (Methodological), vol.57, issue.1, pp.289-300, 1995.

K. P. Chan and A. W. Fu, Efficient time series matching by wavelets, Proceedings of the 15th International Conference on Data Engineering, pp.126-133, 1999.

M. Crouse, R. Nowak, and R. Baraniuk, Wavelet-based statistical signal processing using hidden Markov models, IEEE Transactions on Signal Processing, vol.46, issue.4, pp.886-902, 1998.
DOI : 10.1109/78.668544

I. Daubechies, Orthonormal Bases of Compactly Supported Wavelets II. Variations on a Theme, SIAM Journal on Mathematical Analysis, vol.24, issue.2, pp.499-519, 1993.
DOI : 10.1137/0524031

I. Daubechies, S. Mallat, and A. S. Willsky, Introduction to the spatial issue on wavelet transforms and multiresolution signal analysis, IEEE Trans. Inform. Theory, pp.529-532, 1992.

R. Gencay and F. Selcuk, Asymmetry of Information Flow between Volatilities Across Time Scales, North American Winter Meetings 90, 2004.
DOI : 10.2139/ssrn.386400

A. Kraskov, H. Stogbauer, and P. Grassberger, Estimating mutual information, Physical Review E, vol.69, issue.6, p.66138, 2004.
DOI : 10.1103/PhysRevE.69.066138

URL : http://arxiv.org/abs/cond-mat/0305641

D. Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation, In SIAM Data Mining, 2007.
DOI : 10.1137/1.9781611972771.59

URL : http://arxiv.org/abs/cs/0605103

J. Lin, M. Vlachos, E. Keogh, and D. Gunopulos, Iterative Incremental Clustering of Time Series, 2004.
DOI : 10.1007/978-3-540-24741-8_8

J. Liu and P. Moulin, Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients, IEEE Transactions on Image Processing, vol.10, issue.11, pp.1647-1658, 2001.

S. Mallat, A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.7, pp.674-693, 1989.
DOI : 10.1109/34.192463

M. Misiti, Y. Misiti, G. Oppenheim, and J. Poggi, Clustering Signals Using Wavelets, IWANN, pp.514-521, 2007.
DOI : 10.1007/978-3-540-73007-1_63

P. Pons and M. Latapy, Computing communities in large networks using random walk. Computer and Information Sciences -ISCIS, pp.284-293, 2005.

I. Popivanov and R. J. Miller, Similarity search over time-series data using wavelets, Proceedings 18th International Conference on Data Engineering, p.212, 2002.
DOI : 10.1109/ICDE.2002.994711

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.9016

J. Theiler, S. Eubank, A. Longtin, B. Galdrikian, and J. D. Farmer, Testing for nonlinearity in time series: the method of surrogate data, Physica D: Nonlinear Phenomena, vol.58, issue.1-4, pp.77-94, 1992.
DOI : 10.1016/0167-2789(92)90102-S