E. Hänsler, The hands-free telephone problem-an annotated bibliography, Signal Processing, vol.27, issue.3, pp.259-271, 1992.

W. U. Bajwa, J. Haupt, G. Raz, and R. Nowak, Compressed channel sensing, 42nd Annual Conference on Information Sciences and Systems, 2008.

, IEEE, pp.5-10, 2008.

V. Kocic, D. Brady, and M. Stojanovic, Sparse equalization for realtime digital underwater acoustic communications, OCEANS'95

. Mts/ieee, Challenges of Our Changing Global Environment. Conference Proceedings, vol.3, pp.1417-1422, 1995.

Y. Gu, K. Tang, H. Cui, and W. Du, Convergence analysis of a deficientlength lms filter and optimal-length sequence to model exponential decay impulse response, IEEE Signal Processing Letters, vol.10, issue.1, pp.4-7, 2003.

H. Deng and M. Doroslovacki, Improving convergence of the pnlms algorithm for sparse impulse response identification, IEEE Signal Processing Letters, vol.12, issue.3, pp.181-184, 2005.

J. Benesty and S. L. Gay, An improved pnlms algorithm, IEEE International Conference on Acoustics, Speech, and Signal Processing, vol.2, p.1881, 2002.

D. L. Duttweiler, Proportionate normalized least-mean-squares adaptation in echo cancelers, IEEE Transactions on Speech and Audio Processing, vol.8, issue.5, pp.508-518, 2000.

M. O. Sayin, Y. Yilmaz, A. Demir, and S. S. Kozat, The krylovproportionate normalized least mean fourth approach: Formulation and performance analysis, Signal Processing, vol.109, issue.0, pp.1-13, 2015.

B. Widrow and M. E. Hoff, Adaptive switching circuits, 1960.

E. Walach and B. Widrow, The least mean fourth (lmf) adaptive algorithm and its family, IEEE Transactions on Information Theory, vol.30, issue.2, pp.275-283, 1984.

D. L. Donoho, Compressed sensing, IEEE Transactions on Information Theory, vol.52, issue.4, pp.1289-1306, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00369486

R. Tibshirani, Regression shrinkage and selection via the lasso, Journal of the Royal Statistical Society. Series B (Methodological), pp.267-288, 1996.

Y. Chen, Y. Gu, and A. O. Hero, Sparse lms for system identification, IEEE International Conference on Acoustics, Speech and Signal Processing, pp.3125-3128, 2009.

G. Gui and F. Adachi, Sparse least mean fourth algorithm for adaptive channel estimation in low signal-to-noise ratio region, International Journal of Communication Systems, vol.27, issue.11, pp.3147-3157, 2014.

J. Arenas-garcía, A. R. Figueiras-vidal, and A. H. Sayed, Mean-square performance of a convex combination of two adaptive filters, IEEE Transactions on Signal Processing, vol.54, issue.3, pp.1078-1090, 2006.

M. Silva and V. H. Nascimento, Improving the tracking capability of adaptive filters via convex combination, IEEE Transactions on Signal Processing, vol.56, issue.7, pp.3137-3149, 2008.

B. K. Das and M. Chakraborty, Sparse adaptive filtering by an adaptive convex combination of the LMS and the ZA-LMS Algorithms, IEEE Transactions on Circuits and Systems I: Regular Papers, vol.61, issue.5, pp.1499-1507, 2014.

J. C. Principe, D. Xu, and J. Fisher, Unsupervised adaptive filtering, vol.1, pp.265-319, 2000.

A. H. Sayed, Fundamentals of adaptive filtering, 2003.