S. Barthelmé, N. Tremblay, K. Usevitch, and P. O. Amblard. Determinantal point processes in the flat limit. submitted to AnnAppliedProba 2020.

J. F. Coeurjolly and A. Mazoyer and P. O. Amblard, Monte carlo integration of non differentiable functions on $[0, 1]^i, ι = 1,...,D$, using a single determinantal point pattern defined on $[0, 1]^D$ .in revision for  Electronic Journal of Statistics, January 2020

1.  Y. Y. Pilavci, P. O. Amblard, S. Barthelmé, and N. Tremblay. Graph Tikhonov regularization and inter- polation via random spanning forests. IEEE Trans. On Signal and Information Processing over Networks, 7, 359--374, 2021

2.  A. Komaty, A.-O. Boudraa, P. Flandrin, P.-O. Amblard, and J. Astolfi. On the behavior of memd in presence of multivariate fractional gaussian noise. IEEE Trans. on Sig. Proc., 69:2676–2688, 2021.

3. A. Mazoyer, J. F. Coeurjolly, and P.-O. Amblard. Projections of determinantal point processes. Spatial Statistics, 38:100437, 2020.

4. L. Bosse, et. al... On the nightlow polarisation for space weather exploration. J. Space Weather and Space Climate, 10:35, 2020.

5. N. Tremblay, S. Barthelmé, and P. O. Amblard. Determinantal point processes for coresets. J.Mach. Learn. Res., (20) 1--70   arXiv:1803.08700}, 2019.

6. S. Barthelmé, P. O. Amblard, and N. Tremblay. Asymptotic equivalence of fixed-size and varying-size determinantal point processes. Bernoulli, 25(4B):3555--3589, 2019.

7. S. Chlaily, C. Ren, P. O. Amblard, O. J. J. Michel, P. Comon, and C. Jutten. Information-estimation relationship in mismatched gaussian channels. IEEE Sig. Proc. Letters}, 24(5):688 -- 692, 2017.

8. A. Zebadua, P. O. Amblard, E. Moisan, and O. J. J. Michel. Compressed and quantized correlation estimators. IEEE Transaction on Signal Processing, 65(1):56--68, 2017. arxiv:1511.06639, 2015.
9. J. Manton and P .O. Amblard, A primer on reproducing kernel Hilbert spaces, Foundations and Trends in Signal Processing, Vol. 8: No. 1–2, pp 1-126. 2015. arXiv:1408.095
10. P. O. Amblard, A non-parametric efficient evaluation of partial directed coherence. Biol. Cyber., 109, 203-214, 2015.  arXiv:1311.6345
11. P. O.  Amblard, and O. J. J. Michel,  Causal conditioning and instantaneous coupling in causality graphs. Information Sciences, 264:279--290, 2014.
12. P.O. Amblard and O.J.J. Michel, The relation between Granger causality and directed information
    theory: a review,  Entropy, 15(1):113--143, 2013, arXiv:1211.3169
13. J. Lilensten, M. Barthélémy, P. O. Amblard et. al.,  The thermospheric auroral red line polarization:confirmation of detection and first quantitative analysis. J. Space Weather and Space Climate, 3:A01, 2013.
14. M. McDonnell, F. Li, P. O. Amblard, and A. J. Grant, Optimal sensor selection for noisy binary detection in stochastic pooling networks. Phys. Rev. E, 88:022118, 2013.
15. S. Said and P.O. Amblard and J.H. Manton, Stationary random fields arising from second order partial differential equations oncompact Lie groups, IEEE trans. on Info. Theory, 59(6):3497--3513, 2013.
16. J. F. Coeurjolly and P. O. Amblard and S. Achard, Wavelet analysis of the multivariate fractional Brownian motion,  ESAIM: Probability and Statistics, doi:10.1051/ps/2012011, 17:592--604, 2013.
17. P. O. Amblard and J. F. Coeurjolly and F. Lavancier and A. Philippe, Basic properties of the multivariate fractional Brownian motion, Bulletin Société Mathématique de France, Séminaires et Congrès, 28, 65--87, 2012,  ArXiv1007.0828
18. P. Flandrin and C. Richard and P. O. Amblard and P. Borgnat and P. Honeine and H. Amoud and A. Ferrari and J. Xiao and A. Moghtaderi and P. Ramirez-Cobo, Stationnarité relative et approches connexes, Traitement du Signal  28  691-716  (2011)
19. P. O. Amblard and J. F. Coeurjolly, On the identification of the multivariate fractional Brownian motion, IEEE Trans. on Signal Processing  59  5152--5168  (2011)
20. P. O. Amblard and O. J. J. Michel, On directed information theory and Granger causality graphs, Journal of Computational Neuroscience  30  7--16  (2011)
21. M.D. McDonnell  and P.O. Amblard and N. Stocks, Bio-Inspired Communication: Performance Limits for Information Transmission and Compression in Stochastic Pooling Networks with Binary Quantizing Nodes Journal of Computational and Theoretical Nanoscience, 7:1-10, 2010.
22. M.D. McDonnell, P.O. Amblard, and N.G. Stocks. Stochastic pooling networks. Journal of Statistical Mechanics: Theory and experiment, (2009):P01012, 2009.
23. G. Decrouez, P.O. Amblard, J.M. Brossier, and O. Jones. Galton-watson iterated function systems. J. Phys. A: Math. Theor., 42:095101, 2009.
24. M. Kretzschmar, Th. Dudok de Wit, J. Lilensten, J.F. Hochedez, J. Aboudarham, and F. Auchere P.O. Amblard, and S. Moussaoui. Solar euv/fuv irradiance variations:analysis and observational strategy. Acta geophysica, 57:42--51, 2009.
25. S. Zozor, P. O. Amblard, and C. Duchene. Does the eye tremor provide the hyperacuity phenomenon? Journal of Statistical Mechanics: Theory and experiment,  (2009):P01015, 2009.
    
26. J. Lilensten, J. Moen, M. Barthélémy, R. Thissen, C. Sinmon, D. Lorentzen, O. Dutuit, P.O Amblard, F. Sigernes, Polarization in aurorae: a new dimension for space environments studies,  Geophysical Research Letters, 35:L08804, 2008. 
27. P.O. Amblard, S. Moussaoui, Th. Dudok de Wit, J. Aboudarham, M. Kretzschmar, J. Lilensten, and F. Auchere, The EUV Sun as the superposition of elementary Sun, Astronomy and Astrophysics, 493:L13--L16, 2008.
28. J. Lilensten, T. Dudok de Wit, M. Kretzschmar, P. O. Amblard, S. Moussaoui, L. Aboudarham, and F. Auchere. Reviewon the solar spectral variability in the EUV for space weather studies, Annales Geophysicae, 26, 269--279, 2008.
    
29.  J. Lilensten, T. Dudok de Wit, P. O. Amblard, M. Kretzschmar, L. Aboudarham, and F. Auchere. Recommendation for a set of solar euv lines to be monitored for
      aeronomy applications. Annales Geophysicae, 25:1299--1310, 2007.
30. S. Zozor, P. O. Amblard, and C. Duchene. On pooling networks and fluctuation in suboptimal detection framework. Fluctuation and Noise Letters, 7:39--60, Mar 2007.
31. T. Dudok de Wit, L. Aboudarham, P. O. Amblard, F. Auchere, J. Lilensten, and M. Kretzschmar. Which solar EUV proxies are best for reconstructing the solar EUV
      irradiance?  Adv. Space. Research, Dec 2007.
    
32. P. O. Amblard and C. Vignat. A note on bounded entropies. Physica A: statistical physics and application, 365:50-56, 2006.
33. S. Zozor, J. M. Brossier, and P.O. Amblard. A parametric approach to suboptimal signal detection in
      alpha-stable noise, IEEE Trans. on Signal Processing, 54(12):4497--4509, Dec 2006.
    
34. P. Borgnat, P. O. Amblard, and P. Flandrin. Scale invariances and lamperti transformations for stochastic processes. Journal of Physics, A : math. gen., 38:2081-2101, 2005.
35. S. Zozor and P. O. Amblard. Noise-aided processing: revisiting dithering in a S-D quantizer. IEEE Trans. on Signal Processing, 53(8):3202-3210, Aug 2005.
    
36. T. Dudok de Wit, J. Lilensten, L. Aboudarham, P. O. Amblard, and M. Kretzschmar. Retrieving the solar euv spectrum from a reduced set of spectral lines. Annale Geophysicae, 23:3055-3069, 2005.
    
37. S. Senecal, P. O. Amblard, and L. Cavazzana. Particle filtering equalization method for a satellite communication channel. Journal of Applied Signal Processing, 15:2315-2327, Nov 2004.
    
38. P.O. Amblard, J.M. Brossier, and E. Moisan. Phase tracking : what do we gain from optimality? particle filtering versus phase-locked loops. Signal Processing, 83:151-167, jan 2003.
39. S. Zozor and P. O. Amblard. Stochastic resonance in locally optimal detectors. IEEE Trans. on Signal Processing, 51(12):3177-3181, dec 2003.
40. H. Pedersen, J. Mars, and P.O. Amblard. Improving surface wave group velocity measurements by energy reassignment.  Geophysics, 68, 677-684, 2003.
    
41. S. Zozor and P.O. Amblard. On the use of stochastic resonance in detection. Signal Processing, 82, Mar 2002.
42. S. Senecal and P.O. Amblard. Mcmc blind equalization of a satellite communication system. Journal of Applied Signal Processing, pages 46-57, jan 2002.
43. P. Borgnat, P. Flandrin, and P.O. Amblard. Stochastic discrete scale invariance. IEEE Signal Processing Letters, 9:(6),181-184, june 2002.
    
44. J. Lilensten and P.O. Amblard. On the fast movement of the thermosphere: An interpretation. Annales Geophysicae, 18:1651-1656, 2001.
45. S. Zozor and P.O. Amblard. Stochastic resonance in discrete time nonlinear ar(1) models : erratum. IEEE Trans. on Signal Processing, 51(5):1107-1109, may 2001
46. P. Ravier and P.O. Amblard. Wavelet packets for detecting transient signals. Signal Processing, 81:1909-1926, sep 2001.
    
47. S. Zozor and P.O. Amblard. Stochastic resonance in discrete time nonlinear ar(1) models. IEEE Trans. on Sig. Proc., 49(1):109-120, jan 1999.
48. V. Carmillet, P.O. Amblard, and G. Jourdain. Detection of phase- or frequency-modulated signals in reverberation noise. Journal of the Acoustical Society of America, 6(105):3375-3389, jun 1999.
49. P.O. Amblard and S. Zozor. Cyclostationarity and stochastic resonance in threshold devices. Phys. Rev. E, 5(59):5009-5020, may 1999.
50. P.O. Amblard and J.M. Brossier. On the cascade in fully developed turbulence. the propagator approach versus the markovian description. European Physical Journal B, 12, 579-582, dec 1999.
    
51. P. Ravier and P.O. Amblard. Combining an adapted wavelet analysis with 4th order statistics for transient detection. Signal Processing, 70:115-128, 1998.
52. S. Zozor, E. Moisan, and P.O. Amblard. Revisiting the estimation of the mean using order statistics. Signal Processing, 68, 155-173, 1998.
    
53. P. O. Amblard, M. Gaeta, and J. L. Lacoume. Complex random variables and signals. part 1 : variables. Signal Processing, 42(11):1-13, November 1996.
54. P. O. Amblard, M. Gaeta, and J. L. Lacoume. Complex random variables and signals. part 2 : signals. Signal Processing, 42(11):15-25, November 1996.
55. J. Lilensten and P.O. Amblard. Time-frequency tools of signal processing for eiscat data analysis. Ann. Geophysicae, 14(12):1513-1525, December 1996.
    
56. P. O. Amblard and J.M. Brossier. Adaptive estimation of the fourth-order cumulant of a white stochastic process. Signal Processing, 42(1):37-43, 1995.
    
57. P. O. Amblard and E. Moisan. Frequency domain volterra filters in terms of distributions. IEEE Sig. Proc. Letters, 1(11):169-172, November 1994.
58. P. O. Amblard and J. L. Lacoume. A deductive construction of third-order time-frequency distributions. Signal Processing, 36(3):277-286, 1994.
    
    
    

1. P.-O. Amblard. Résonance stochastique Assemblée générale du GdR ISIS, mai 2001. (in french, a flavor of stochastic resonance)
2. P.-O. Amblard. Le bruit peut-il devenir un allié? Traitements de l'information favorisés par le bruit, Exposition de Physique, Entretiens Physique-Industrie : Le Bruit, 17 juin 2004
3. C. Duchêne, P. O. Amblard, and S. Zozor. Quantizer based suboptimal detectors: noise-enhanced performance and robustness. In 3rd SPIE conf. on Noise and Fluctuations, Austin, USA, vol. 5847, Invited Talk, pages 100-110, May 2005.
4. J. Lilensten, T. Dudok de Wit, M.  Kretzschmar, P.O.  Amblard, S. Moussaoui, J. Aboudarham ,  F. Auchere,  Retrieving the EUV solar spectrum from a selected set of lines for space weather purposes: A review of theories, models and experiments, invited conference , European Space Weather Week, nov 2006, Bruxelles
5. M. McDonnell, P. O. Amblard, N. Stocks, S. Zozor, and D. Abbott. High resolution optimal quantization for stochastic pooling networks. SPIE conference on Complexity and nonlinear dynamics
     systems, vol. 6417, Invited Talk, pages 100--110, December 2006.
6. P.O. Amblard, S. Zozor,  M. McDonnell and N. Stocks,  Pooling networks for a discrimination task: noise-enhanced detection. 4rd SPIE conf. on Noise and Fluctuations, Firenze, Italia,
     vol., Invited Talk, 2007.
7. C. Villard, P.O. Amblard, G. Becq, S. Gory-Faure, and S. Roth. Living ordered neural networks as model systems for signal processing.4rd SPIE conf. on Noise and Fluctuations, Firenze, Italia,
   Invited Talk, 2007.
8. Jean Lilensten, Mathieu Barthélemy, Roland Thissen, Jøran Moen, Cyril Simon, Dag A.
   Lorentzen, Odile Dutuit, Pierre Olivier Amblard, Fred Sigernes,  Polarization in aurorae: a new dimension for space environments studied, 
   invited conference at the Space Research Centre Polish Academy of Sciences, april 2008, Varsaw, Poland
9. P.O. Amblard and O.J.J. Michel,  Networks of signals, directed information and causality graphs,
   Invited Seminar, SEMOVI, GIN,  Grenoble, France, 7 decembre 2011
10. P.O. Amblard and O.J.J. Michel, On Granger causality and directed information theory, 1st Workshop on directed information theory, Munich, Germany, May 6-8, 2012.

1. J.M. Brossier and P.-O. Amblard. Introduction aux problèmes de synchronisation, ECOTEL, Nice, octobre 2000 (in french, stuff on synchronisation techniques)
   

1. P. O. Amblard, D. Baudois, and C. Servière. Soustraction de bruit en situation non linéaire utilisant les filtres de volterra. In Proc. GRETSI, pages 325-328, Juans-Les-Pins, Sep - 1991.
2. P. O. Amblard, D. Baudois, and J.L. Lacoume. Edgeworth series expansion of the conditional mean and the optimality of non-linear volterra filters. In Proc. ICASSP, pages V477-V480, San Francisco, March 1992.
3. J. L. Lacoume, M. Gaeta, and P. O. Amblard. From order 2 to HOS: new tools and applications. In Proc. European Signal Processing Conf. EUSIPCO, pages 91-98, Brussels, Aug 24 - 27 1992.
4. P. O. Amblard and J.L. Lacoume. Construction of fourth-order cohen's class : a deductive approach. In IEEE symposium on Time-Scale and Time-Frequency Analysis, Victoria, Canada, October 1992.
5. P. O. Amblard and D. Baudois. Non-linear noise cancellation using volterra filters : a real case study. In IEEE workshop on Nonlinear Digital Signal Processing, pages 2.1-1.1-1.5, Tampere, Finland, January 1993.
6. P. O. Amblard, J. L. Lacoume, and J. M. Brossier. Transient detection, higher-order time-frequency distributions and the entropy. In Proc. IEEE SP Workshop on Higher-Order Stat., Lake Tahoe, USA, pages 265-269, 1993.
7. P. O. Amblard and J. L. Lacoume. Statistiques d'ordre supérieur des signaux complexes stationnaires et non-stationnaires. In Proc. GRETSI, pages 121-124, 1993.
8. P. O. Amblard, J. M. Brossier, and N. Charkani. New adaptive estimation of the fourth-order cumulant... In Proc. EUSIPCO, pages 466-469, Edinburgh, September 1994.
9. K. Mio, E. Moisan, and P.O. Amblard. Nonlinear noise cancellation: Bilinear filtering of a sonar experiment. In IEEE Workshop on nonlinear signal and image processing, pages 416-419, Halkidiki, Greece, 20-22 June 1995.
10. P.O. Amblard and E. Moisan. On the use of frequency domain volterra filters. In IEEE Workshop on nonlinear signal and image processing, pages 380-383, Halkidiki, Greece, 20-22 June 1995.
11. P.O. Amblard and P. Ravier. Experimental performance analysis of an on-line transient detector. In IEEE Workshop on HOS, pages 171-175, Gerona, Spain, 12-14 June 1995.
12. P. Marchand, P. O. Amblard, and J.L. Lacoume. Statistiques d'ordre supérieur à deux pour des signaux cyclostationnaires à valeurs complexes. In Proc. GRETSI, Juans-Les-Pins, pages 69-72, 1995.
13. L. Duboisset, P. Ravier, and P. O. Amblard. Etudes des performances de détecteurs de transitoires fondés sur les statistiques d'ordre supérieurs et les transformées linéaires. In Proc. GRETSI, Juans-Les-Pins, pages 1169-1171, 1995.
14. P. O. Amblard and P. Duvaut. Filtrage adapté dans le cas gaussien complexe non circulaire. In Proc. GRETSI, Juans-Les-Pins, pages 141-144, 1995.
15. V. Pierson and P. O. Amblard. Studying the performances of linear signature detector on a time-frequency representation. In Proc. IEEE digital signal processing, September 1996.
16. P. Ravier and P. O. Amblard. Using malvar wavelets for transient detection. In IEEE symposium on time-frequency and time-scale analysis, Paris, France, pages 229-232, June 1996.
17. P. Ravier and P. O. Amblard. A transient detector based on malvar wavelets. In IEEE Ocean, Fort Lauderdale, USA, September 1996.
18. S. Zozor and P. O. Amblard. Stochastic resonance in a discrete time nonlinear setar(1,2,0,0) model. In Proc. IEEE workshop on HOS, Banff, Canada, pages 166-170, 1997.
19. P. O. Amblard, J.M. Brossier, and J.L. Lacoume. Playing with long range dependence and hos. In Proc. IEEE workshop on HOS, Banff, Canada, pages 453-457, 1997.
20. S. Zozor and P. O. Amblard. Résonance stochastique via des setar (1,n, 0,...,0) discrets non linéaires. In Proc. GRETSI, Juans-Les-Pins, pages 773-776, 1997.
21. S. Zozor, E. MOISAN, and P. O. Amblard. Estimation de la moyenne et statistiques d'ordre. In Proc. GRETSI, Juans-Les-Pins, pages 507-510, 1997.
22. P. Ravier and P. O. Amblard. Denoising using wavelet packets and the kurtosis: Application to transient detection. In Proc. IEEE symposium on time-frequency and time-scale analysis, Pitsburgh, USA, pages 625-628, 1998.
23. S. Zozor and P. O. Amblard. Stochastic resonance in a discrete time nonlinear system with cyclostationarity inputs. In Proc. Physics in signal Processing, Paris, France, pages -, 1999.
24. S. Zozor and P. O. Amblard. 2-dimensional stochastic resonance in a discrete time nonlinear system with an elliptic input. In Proc. IEEE workshop on nonlinear signal processing, Antalya, Turquie, pages 95-99, jun 1999.
25. P. O. Amblard and O. Michel. On higher-order affine distributions. In Proc. IEEE workshop on HOS, Caesaera, Israël, pages 273-276, 1999.
26. P. O. Amblard and O. Michel. Vers des représentations affines multilinéaires. In Proc.colloque GRETSI, Vannes, Tome 1, pages 19-22, 1999.
27. S. Zozor and P. O. Amblard. Qu'en-est-il de la résonance stochastique comme outil potentiel en traitement du signal. In Proc.colloque GRETSI, Vannes, Tome 2, pages 451-454, 1999.
28. J. Mars, P. O. Amblard, H. Pedersen, and A.L. Bard. Réallocation énergétique pour l'analyse par filtrage multiple. application à la mesure de courbe de dispersion de séismes. In Proc.colloque GRETSI, Vannes, Tome 2, pages 343-346, 1999.
29. S. Zozor and P. O. Amblard. Can stochastic resonance be used in detection. In to appear in Proc.EUSIPCO, Tampere, Finland, pages -, 2000.
30. S. Senecal and P. O. Amblard. Bayesian separation of discrete sources via Gibbs sampling. In Proc. ICA, Helsinki, Finland, pages 561-566, 2000.
31. S. Senecal and P. O. Amblard. Mcmc methods for discrete sources separation. In Bayesian inference and maximum entropy methods in science and engineering, Proc. MaxEnt'00, Gif-sur-Yvette, France, pages 350-360, 2001.
32. S. Senecal and P. O. Amblard. Mcmc methods non linear channel equalization. In Proc. IEEE NSIP, USA, CD Rom, 2001.
33. S. Zozor and P. O. Amblard. Les détecteurs localement optimaux sont -ils des résonateurs stochastiques. In Proc. GRETSI, Toulouse, France, pages 703-706, 2001.
34. P. O. Amblard, J.M. Brossier, and E. Moisan. Poursuite d'une phase brownienne à dérive linéaire. performances et algorithmes. In Proc. GRETSI, Toulouse, France, pages 203-206, 2001.
35. S. Senecal and P. O. Amblard. Méthodes de simulation pour la séparation de sources discrètes. In Proc. GRETSI, Toulouse, France, pages 319-322, 2001.
36. P. Borgnat, P. Flandrin, and P.O. Amblard. Une approche statistique de l'invariance d'échelle discrète. In Proc. GRETSI, Toulouse, France, pages 29-32, 2001.
37. P. Borgnat, P. Flandrin, and P.O. Amblard. Stochastic discrete scale invariance. In Proc. IEEE workshop on ssp, Singapore, pages66-69, 2001.
38. P. O. Amblard, J.M. Brossier, and E. Moisan. Tracking a brownian phase with linear drift: algorithms and performances. In Proc. EUSIPCO, Toulouse, France, CD-ROM, 2002.
    
39. J.M. Brossier, P. O. Amblard, and B. Geller. Self-adaptive PLL for general QAM constellations. In Proc. EUSIPCO, Toulouse, France, CD-ROM, 2002.
    
40. P. Borgnat, P. O. Amblard, and P. Flandrin. Random processes with discrete scale invariance: Methods of synthesis. In Symp. Self-similarity and Applications, Clermont-Ferrand France, 2002.
    
41. P. Borgnat, P. O. Amblard, and P. Flandrin. Generalized lamperti transformation of broken scale invariance. In ASILOMAR conf. on Signal, Systems and Computers, 2002.
    
42. P. Borgnat, P. O. Amblard, and P. Flandrin. Lamperti transformation for finite size scale invariance. In proc. Physics in Signal and Image Processing, PSIP 2003, Grenoble, France, pages 177-180, 2003.
    
43. S. Zozor and P. O. Amblard. Stochastic resonance in terms of detection. In proc. Physics in Signal and Image Processing, PSIP 2003, Grenoble, France, pages 153-156, 2003.
    
44. S. Zozor and P. O. Amblard. Stochastic resonance in a sigma-delta quantizer. In proc. IEEE workshop Nonlinear Digital Signal and Image Processing, Grado, Italy, CD ROM, 2003.
    
45. S. Zozor and P. O. Amblard. On stochastic resonance-like effects in detection. In SPIE conf. on Noise and Fluctuations, Santa Fé, USA, vol. 5114, pages 161-172, 2003.
    
46. P. O. Amblard, P. Borgnat, and P. Flandrin. Stochastic processes with finite size scale invariance. In SPIE conf. on Noise and Fluctuations, Santa Fé, USA, vol. 5114, pages 161-172, 2003.
    
47. S. Senecal and P.O. Amblard and L. Cavazzanna. In proc ICASSP, Hong-Kong, cancelled because of SRAS, cdrom, 2003.
    
48. P. Borgnat, P. O. Amblard, and P. Flandrin. Invariance d'échelle brisée et accroissements stationnaires. In proc.GRETSI 2003, Paris, France, cd rom, 2003.
49. J.M. Brossier and  P. O. Amblard". Particulaire et communications numériques, Journées SEE Signal et communications numériques, juin 2004 ( in french , Particle filtering and digital communications)
    
50. P. O. Amblard and N. Le Bihan. On properness of quaternion valued random variables. In IMA conf. on mathematics in signal processing, Cirencester, UK, dec 2004.
    
51. P. O. Amblard and P. Borgnat. Discrete scale invariance : renormalization group and iterated function systems. In IMA conf. on mathematics in signal processing, Cirencester, UK, dec 2004.
    
52. C. Duchêne, S. Zozor, and P. O. Amblard. Noise-aided suboptimal quantizer-decision systems. In proc. Physics in Signal and Image Processing, PSIP 2005, Toulouse, France, pages 43-48, 2005.
    
53. A. Voicila, C. Duchêne, S. Zozor, J.M. Brossier, and P. O. Amblard. On a suboptimal detector in a-stable context. In proc. Physics in Signal and Image Processing, PSIP 2005, Toulouse, France, pages 289-294, 2005.
    
54. C. Duchêne, P. O. Amblard, and S. Zozor. Quantizer based suboptimal detectors: noise-enhanced performance and robustness. In 3rd SPIE conf. on Noise and Fluctuations, Austin, USA, vol. 5847, Invited Talk, pages 100-110, May 2005.
    
55. P. O. Amblard, O. MichelL, and S. Morfu. Revisiting the asymmetric binary channel: joint noise-enhanced detection and information transmission through threshold devices. In 3rd SPIE conf. on Noise and Fluctuations, Austin, USA, vol. 5845, pages 50-60, May 2005.
    
56. S. Zozor, J.M. Brossier, P. O. Amblard, C. Duchêne, and A. Voicila. About suboptimal detection in a-stable noise. In 3rd SPIE conf. on Noise and Fluctuations , Austin, USA, vol. 5847, pages 111-120, 2005.
    
57. P. O. Amblard and C. Vignat. A note on bounded entropies. In NEXT2005, News, EXpectations and Trends in Statistical Physics, pages -, 2005.
    
58. C. Duchêne, S. Zozor, and P. O. Amblard. Détection sous-optimale et quantifieurs stochastiques. In proc.GRETSI 2005, Louvain-La-Neuve, Belgique, page CDROM, 2005.
    
59. S. Zozor, J.M. Brossier, and P. O. Amblard. Détection sous-optimale dans du bruit a-stable. In proc.GRETSI 2005, Louvain-La-Neuve, Belgique, page CDROM, 2005.
    
60. P. O. Amblard, S. Zozor, and O.J.J. Michel. Networks of the pooling type and optimal quantization. In proc.ICASSP 2006, Toulouse, France, page CDROM, 2006.
61. P. O. Amblard, O. Michel, and S. Morfu. Detection and information points of view in threshold devices. In proc. Nonlinear Dynamical Electronic Sysems, NDES 2006, Dijon, France, June 2005.
62. S. Gory-Faure, J. Brocard, P.O. Amblard, A. Depaulis, P. Salin, E. Dumas, S. Roth, and C.Villard. Ordered neural networks grown on patterned mea. In  proc. MEA Meeting, Reutingen, Germany, pages pp194--195, July 2006.
63. M. McDonnell, P. O. Amblard, N. Stocks, S. Zozor, and D. Abbott. High resolution optimal quantization for stochastic pooling networks. In  SPIE conference on Complexity and nonlinear dynamics systems, vol. 6417, pages 100--110, December 2006.
64. N. Le Bihan and P. O. Amblard. Detection and estimation of gaussian proper quaternion valued random
      processes. In proc. IMA conf. on mathematics in signal processing, Cirencester, UK, pages 23--26, dec 2006.
65. G. Decrouez, P. O. Amblard, and J.M. Brossier. A wavelet analysis of random iterated function systems. In proc. IMA conf. on mathematics in signal processing,
      Cirencester, UK, pages 14--17, dec 2006.
66. S. Zozor, P. O. Amblard, and C. Duchêne. On the microsaccades in the retina as a noice-enhanced processing. In  proc. Physics in Signal and Image Processing, PSIP 2007 Mulhouse, France, cdrom, 2007
67. G. Decrouez, P. O. Amblard, J.M. Brossier, and O. JONES. Galton-watson random fractals. In proc. IEEE ICASSP 2007, Hawaï, USA, cdrom, 2007.
68. P.O. Amblard, S. Zozor,  M. McDonnell and N. Stocks, Pooling networks for a discrimination task: noise-enhanced detection. In  4rd SPIE conf. on Noise and Fluctuations, Firenze, Italia,
      CDROM  vol .6600-6603, 2007.
69. C. Villard, P.O. Amblard, G. Becq, S. Gory-Faure, and S. Roth. Living ordered neural networks as model systems for signal  processing. In  4rd SPIE conf. on Noise and Fluctuations, Firenze, Italia,
     CDROM vol .6600-6603, 2007
70. S. Zozor, P.O. Amblard, and C.Duchêne. Fluctuation in the retina: noise-enhanced processing via random sampling and microsaccads. In 4rd SPIE conf. on Noise and Fluctuations, Firenze, Italia,
     CDROM vol .6600-6603, 2007
71. S. Zozor, P. O. Amblard, and C. Duchêne. Echantillonnage aléatoire de la rétine et micro-saccades:
      amélioration du traitement de l'information par le bruit ? In GRETSI 2007, Troyes, France, 2007.
72. G. Decrouez, P. O. Amblard, J. M. Brossier, and O. JONES. Systèmes de fonctions itérés aléatoires sur des arbres de  galton-watson. In  GRETSI 2007, Troyes, France, 2007.
73. P. O. Amblard, S. Moussaoui, T. Dudok de Wit, J. Lilensten, M. Kretzschmar,
      L. Aboudarham, and F. Auchere. Le soleil comme superposition de soleils élémentaires. In GRETSI 2007, Troyes, France, 2007.
74. E. Diaz, R. Escola, P.Pham, R.Guillemaud, G.Becq, P.-O. Amblard, and C. Villard. Recording and simulation of hippocampal neural networks. In MEA 2008, 2008.
    
75. P.O. Amblard and O.J.J. Michel. Information flow through scales. In  IMA conf on Maths and Signal processing, pp78, 2008.
    
76. P.O. Amblard, S. Zozor, O.J.J. Michel, and A.M. Cuculescu. On the estimation of the entropy using k-th nearest neighbors.  In IMA Conf. on Maths and Signal Processing, pp 79-82, 2008.
    
77. G. Becq, P.-O. Amblard, S. Roth, and C. Villard. Simulation of hippocampal neural networks under bicuculline, with noise and synaptic delays. In Neurocomp 2008, 2008.
    
78. G. Becq, S. Roth, S. Zozor, J. Brocard, S. Gory-Faure, P.-O. Amblard, and C. Villard. Recording and simulation of hippocampal neural networks with bicuculline. In  MEA 2008, 2008.
    
79. P. O. Amblard and O. J. J. Michel.Sur différentes mesures de dépendance causales entre signaux aléatoires (On different measures of causal dependencies between random signals);  In proc. Gretsi, Dijon, France, Sept., 2009.
    
80. P. O. Amblard, S. Achard, J. Lemoine, and C. Gouy-Paillé. Retrieving connectivity in complex networks of long range dependent stochastic processes. In European Conference on Complex Systems Warwick, UK,, CD ROM, Track F - Mathematics and Simulation, p76, 2009.
    
81. J. Lemoine, C. Gouy-Pailler, S. Achard, and P. O. Amblard. Recherche de la connectivité de réseaux complexes. application en  irmf. In proc. Gretsi, Dijon, France, Sept., 2009.
82. J. F. Coeurjolly and P. O. Amblard and S. Achard, On multivariate fractional Brownian motion and multivariate fractional Gaussian noise, Proc. EUSIPCO, Coppenhague, 2010.
83. P. O. Amblard and O. J. J. Michel, Information dirigée et graphes de causalité au sens de Granger, In proc. Gretsi, Bordeaux, France, Sept., 2011.
84. P. O. Amblard and J. F. Coeurjolly, Identification du mouvement Brownien fractionnaire multivarié,  In proc. Gretsi, Bordeaux, France, Sept., 2011.
85. F. Chatelain and S. Achard and C. Gouy-Pailler and O. J. J. Michel and P. O. Amblard, In proc. Graphe de connectivité cérébrale et longue dépendance,  Gretsi, Bordeaux, France, Sept., 2011.
86. P. O. Amblard and O. J. J. Michel, Causal conditioning and instantaneous coupling in causality graphs, In Proc. IEEE SSP, Annn Arbor, Michigan, August 2012.
87. P.-O. Amblard and O. J. J. Michel and C.Richard and P. Honeine, A Gaussian Process Regression approach for testing Granger causality between time series data, In Proc. ICASSP, Osaka, Japan, March 2012.
    
88. P. O. Amblard and R. Vincent and O. J. J. Michel and C. Richard, Kernelizing Geweke's measure of Granger causality, IEEE Symposium MLSP, Spain,  (2012)
89. S. Said and J. Manton and P.-O. Amblard, On a class of filtering problems with observation in a Riemannian manifold, proc. MTSN, Melbourne, Australia, 2012
90. P.O. Amblard and J.H. Manton, On data sparsification and a recursive algorithm for estimating a
      kernel-based measure of independence. proc. ICASSP, Vancouver, Canada, 2013.
91. P.O. Amblard., Versions r{\'e}cursives et adaptatives d'une mesure
      d'indépendance. GRETSI 2013, Brest, France, 2013
92. P.O. Amblard and O.~J.~J. Michel,  Causalité de granger pour les signaux à valeurs fonctionnelles.
      GRETSI 2013, Brest, France, 2013.
93. G. Decrouez, P.O. Amblard, and O. Jones, Estimation of the multifractal spectrum using the crossing tree.
     GRETSI 2013, Brest, France, 2013.
94. A. Zebadua, O.J.J. Michel, P.O. Amblard, E. Moisan, Signal  processing with coarse-quantized measurements: efficient cross-correlation estimation, Proc. IMA conf on Math. and Sig. Proc., Birmingham, UK, dec 2014.
95. P.O. Amblard and O.J.J. Michel, Granger causality for functional valued random processes, Proc. ISITA, Melbourne, Australia, Oct. 2014.
96. G. Decrouez and P. O. Amblard, Analysis of H-sssi processes using the crossing tree: an alternative to wavelets, Proc. ICASSP, Brisbane, Australia, April 2015.
97. P. O. Amblard and H. Kadri. Operator-valued kernel recursive least squares algorithm. In Proc. EUSIPCO, Nice, France, 2015.
98. G. Decrouez and P. O. Amblard. Crossing tree partition functions. In Proc. EUSIPCO, Nice, France, 2015.
99. P. O. Amblard and H. Kadri. Algorithme LMS pour la régression à noyau multivariée parcimonieuse. In GRETSI 2015, Lyon, France, 2015.
100. A. Zebadua, P. O. Amblard, E. M. O. J. J. Michel, M. Carmona, A. Paleologue, and M. Billere. Examples of output-only modal identification using compressive sensing techniques. In IWSHM 2015, Stanford, USA, 2015.
101. A. Zebadua, P. O. Amblard, E. Moisan, and O. J. J. Michel. Estimation de corrélation sur signaux compressés. In GRETSI 2015, Lyon, France, 2015.
       
     
     

1. P. O. Amblard, Higher-order statistics for nonstationary signals. International Congress on Industrial and Applied Mathematics, Hambourg, juin 1995.
2. H. A. Pedersen, J. I. Mars, P. O. Amblard and A. L. BARD, Improving precision of frequency time analysis of surface wave, XXII General Assembly of the International Union of Geodesy and Geophysics, ST5, Birmingham, 18-30 juillet 1999.
3. J. Lilensten and P. O. Amblard, Fast movement of the thermosphere : Eddies? Prague, july 2000.
4. J. Aboudarham, P.O. Amblard, T. Dudok de Wit, J. Lilensten and M. Kretzschmar Reconstruction du spectre EUV solaire à partir d'un nombre limité de raies spectrales, conférence MEDOC-SOHO, Paris, octobre 2004.
   
5. J. Aboudarham, P.O. Amblard, T. Dudok de Wit, J. Lilensten and M. Kretzschmar Retrieving the solar EUV spectrum from a reduced set of spectral lines, First European Space Weather Week, ESTEC-ESA, 29 Nov 2004 - 3 dec 2004.
6. J. Lilensten and M. Barthélémy and P.-O. A. et al, Calibrated polarization parameters of the auroral red line in Hornsund, EGU Vienna,  (2012)
   
 

Poly de cours :


(Transl: lecture notes)
  


Fractales? cours DEA SIPT (in french)  et les transparents de cours (3 fichiers) 1 2 et 3

Notes de cours de traitement du signal, Master 2 R

Cours sur les RKHS en traitement du signal.