Bibliography

Major publications by the team in recent years

• 1G. Attuel, E. G. Gerasimova-Chechkina, F. Argoul, H. Yahia, A. Arnéodo.
  
  Multifractal desynchronization of the cardiac excitable cell network during atrial fibrillation. I. Multifractal analysis of clinical data, in: Frontiers in Physiology, March 2018, vol. 8, pp. 1-30. [ DOI : 10.3389/fphys.2017.01139 ]
  
  https://hal.inria.fr/hal-01673364
• 2H. Badri, H. Yahia.
  
  A Non-Local Low-Rank Approach to Enforce Integrability, in: IEEE Transactions on Image Processing, June 2016, 10 p.
  
  https://hal.inria.fr/hal-01317151
• 3H. Badri, H. Yahia, K. Daoudi.
  
  Fast and Accurate Texture Recognition with Multilayer Convolution and Multifractal Analysis, in: European Conference on Computer Vision, Zürich, Switzerland, ECCV 2014, September 2014.
  
  https://hal.inria.fr/hal-01064793
• 4I. Hernández-Carrasco, V. Garçon, J. Sudre, C. Garbe, H. Yahia.
  
  Increasing the Resolution of Ocean pCO₂ Maps in the South Eastern Atlantic Ocean Merging Multifractal Satellite-Derived Ocean Variables, in: IEEE Transactions on Geoscience and Remote Sensing, June 2018, pp. 1 - 15. [ DOI : 10.1109/TGRS.2018.2840526 ]
  
  https://hal.inria.fr/hal-01825810
• 5I. Hernández-Carrasco, J. Sudre, V. Garçon, H. Yahia, C. Garbe, A. Paulmier, B. Dewitte, S. Illig, I. Dadou, M. González-Dávila, J. Santana Casiano.
  
  Reconstruction of super-resolution ocean pCO 2 and air-sea fluxes of CO 2 from satellite imagery in the Southeastern Atlantic, in: Biogeosciences, September 2015, 20 p, This work is a contribution to ESA Support To Science Element Grant N◦ 400014715/11/I-NB OceanFlux- Upwelling Theme. The Surface Ocean CO2 Atlas (SOCAT) is an international effort, supported by the International Ocean Carbon Coordination Project (IOCCP), the Surface Ocean Lower Atmo- sphere Study (SOLAS), and the Integrated Marine Biogeochem- istry and Ecosystem Research program (IMBER), to deliver a uni- formly quality-controlled surface ocean CO2 database. The many researchers and funding agencies responsible for the collection of data and quality control are thanked for their contributions to SO- CAT.
  
  https://hal.inria.fr/hal-01193339
• 6V. Khanagha, K. Daoudi, H. Yahia.
  
  Detection of Glottal Closure Instants based on the Microcanonical Multiscale Formalism, in: IEEE Transactions on Audio, Speech and Language Processing, December 2014.
  
  https://hal.inria.fr/hal-01059345
• 7V. Khanagha, K. Daoudi, H. Yahia.
  
  Efficient and robust detection of Glottal Closure Instants using Most Singular Manifold of speech signals, in: IEEE Transactions on Acoustics Speech and Signal Processing, 2014, forthcoming.
  
  https://hal.inria.fr/hal-00802014
• 8S. Maji, H. Yahia, T. Fusco.
  
  A Multifractal-based Wavefront Phase Estimation Technique for Ground-based Astronomical Observations, in: IEEE Transactions on Geoscience and Remote Sensing, November 2015, 11 p. [ DOI : 10.1109/TGRS.2015.2487546 ]
  
  https://hal.inria.fr/hal-01254482
• 9S. K. Maji, H. Yahia.
  
  Edges, Transitions and Criticality, in: Pattern Recognition, January 2014.
  
  http://hal.inria.fr/hal-00924137
• 10O. Pont, A. Turiel, H. Yahia.
  
  Singularity analysis in digital signals through the evaluation of their Unpredictable Point Manifold, in: International Journal of Computer Mathematics, 2012.
  
  http://hal.inria.fr/hal-00688715
• 11O. Pont, H. Yahia, R. Dubois, M. Haïssaguerre.
  
  A Singularity-analysis Approach to characterize Epicardial Electric Potential, in: Computing in Cardiology , 2012.
  
  http://hal.inria.fr/hal-00750003
• 12J. Sudre, H. Yahia, O. Pont, V. Garçon.
  
  Ocean Turbulent Dynamics at Superresolution From Optimal Multiresolution Analysis and Multiplicative Cascade, in: IEEE Transactions on Geoscience and Remote Sensing, June 2015, vol. 53, n^o 11, 12 p. [ DOI : 10.1109/TGRS.2015.2436431 ]
  
  https://hal.inria.fr/hal-01166170
• 13A. Turiel, H. Yahia, C. Perez-Vicente.
  
  Microcanonical multifractal formalism: a geometrical approach to multifractal systems. Part I: singularity analysis, in: Journal of Physics A: Math. Theor, 2008, vol. 41.
  
  http://dx.doi.org/10.1088/1751-8113/41/1/015501
• 14H. Yahia, J. Sudre, C. Pottier, V. Garçon.
  
  Motion analysis in oceanographic satellite images using multiscale methods and the energy cascade, in: Pattern Recognition, 2010, vol. 43, pp. 3591-3604.
  
  http://dx.doi.org/10.1016/j.patcog.2010.04.011

Publications of the year

Articles in International Peer-Reviewed Journals

• 15G. Attuel, E. G. Gerasimova-Chechkina, F. Argoul, H. Yahia, A. Arnéodo.
  
  Multifractal desynchronization of the cardiac excitable cell network during atrial fibrillation. I. Multifractal analysis of clinical data, in: Frontiers in Physiology, March 2018, vol. 8, pp. 1-30. [ DOI : 10.3389/fphys.2017.01139 ]
  
  https://hal.inria.fr/hal-01673364
• 16A. El Aouni, K. Daoudi, H. Yahia, K. Minaoui, A. Benazzouz.
  
  Surface mixing and biological activity in the North-West African upwelling, in: Chaos, January 2019, vol. 29, n^o 1, 011104 p.
  
  https://hal.inria.fr/hal-01985164
• 17I. Hernández-Carrasco, V. Garçon, J. Sudre, C. Garbe, H. Yahia.
  
  Increasing the Resolution of Ocean pCO₂ Maps in the South Eastern Atlantic Ocean Merging Multifractal Satellite-Derived Ocean Variables, in: IEEE Transactions on Geoscience and Remote Sensing, June 2018, pp. 1 - 15. [ DOI : 10.1109/TGRS.2018.2840526 ]
  
  https://hal.inria.fr/hal-01825810
• 18A. Tamim, K. Minaoui, K. Daoudi, H. Yahia, A. Atillah, S. E. Fellah, D. Aboutajdine, M. E. Ansari.
  
  Automatic Detection of Moroccan Coastal Upwelling Zones using Sea Surface Temperature Images, in: International Journal of Remote Sensing, October 2018.
  
  https://hal.inria.fr/hal-01881880
• 19H. Yahia, J. Sudre, C. Maes, V. Garçon.
  
  Effect of wind stress forcing on ocean dynamics at air-sea interface, in: Frontiers of Information Technology & Electronic Engineering, August 2018, vol. 19, n^o 8. [ DOI : 10.1631/FITEE.1700797 ]
  
  https://hal.inria.fr/hal-01884543

International Conferences with Proceedings

• 20A. El Aouni, K. Daoudi, H. Yahia, K. Minaoui.
  
  Coherent Vortex Detection from Particles Trajectories Analysis, in: 2018 SIAM Conference on Nonlinear Waves and Coherent Structures, Anaheim, United States, June 2018.
  
  https://hal.inria.fr/hal-01699903
• 21A. El Aouni, K. Daoudi, H. Yahia, K. Minaoui.
  
  Surface Mixing and Biological Activity in The North African Upwelling, in: AGU Ocean Sciences Meeting 2018, Portland, Oregon, United States, February 2018.
  
  https://hal.inria.fr/hal-01627958
• 22G. Li, K. Daoudi, J. Klempir, J. Rusz.
  
  Linear classification in speech-based objective differential diagnosis of parkinsonism, in: IEEE-ICASSP - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, Calgary, Canada, April 2018.
  
  https://hal.inria.fr/hal-01696617

Conferences without Proceedings

• 23N. Brodu.
  
  Low-rankness transfer for denoising Sentinel-1 SAR images, in: ISIVC'2018 - 9th International Symposium on Signal, Image, Video and Communications, Rabat, Morocco, November 2018.
  
  https://hal.archives-ouvertes.fr/hal-01936331
• 24N. Schneider, R. Simon, S. Bontemps, A. Roy, L. Bonne, H. M. Yahia, G. Attuel.
  
  The GENESIS project, in: Proceedings of the Annual meeting of the French Society of Astronomy and Astrophysics. SF2A-2018: 3 au 6 juillet 2018 – Bordeaux-France- Eds.: P. Di Matteo, F. Billebaud, F. Herpin, N. Lagarde, J.-B. Marquette, A. Robin, O. Venot, pp.179-180, Bordeaux, France, July 2018.
  
  https://hal.archives-ouvertes.fr/hal-01978395
• 25G. Singh Phartiyal, N. Brodu, D. Singh, H. Yahia.
  
  A mixed spectral and spatial Convolutional Neural Network for Land Cover Classification using SAR and Optical data, in: EGU General Assembly 2018, Vienne, Austria, April 2018, vol. 20, 12647 p.
  
  https://hal.archives-ouvertes.fr/hal-01693650

Other Publications

• 26L. Bonne, S. Bontemps, N. Schneider, T. Csengeri, H. Yahia, R. Güsten, G. Attuel, A. Roy, R. Simon.
  
  Search for filamentary accretion through low velocity shocks, March 2018, poster.
  
  https://hal.inria.fr/hal-01724386
• 27A. El Aouni, K. Minaoui, K. Daoudi, H. Yahia.
  
  North-West African Upwelling dynamics from physical and biological satellite observations, July 2018, Report of the 4th GEO Blue Planet Symposium, Poster.
  
  https://hal.inria.fr/hal-01968269

References in notes

• 28M. A. Allessie.
  
  Atrial electrophysiologic remodeling : another vicious circle ?, in: J. Cardiovasc. Electrophysiol., 1998, vol. 9, pp. 1378–1393.
• 29M. A. Allessie, I. F. Bonke, F. J. Schopman.
  
  Circus movement in rabbit atrial muscle as a mechanism of tachycardia, in: Circ. Res., 1977, vol. 41, pp. 9–18.
• 30A. Arnéodo, F. Argoul, E. Bacry, J. Elezgaray, J. F. Muzy.
  
  Ondelettes, multifractales et turbulence, Diderot Editeur, Paris, France, 1995.
• 31R. Arora.
  
  Recent Insights Into the Role of the Autonomic Nervous System in the Creation of Substrate for Atrial Fibrillation, in: Circ. Arrhythm. Electrophysiol., 2012, vol. 5, pp. 859–859.
• 32P. Attuel, et al..
  
  Failure in the rate adaptation of the atrial refractory period: its relationship to vulnerability, in: Int. J. Cardio., 1982, vol. 2, n^o 2, pp. 179–197.
• 33P. Attuel, et al..
  
  Latent atrial vulnerability: new means of electrophysiologic investigations in paroxysmal atrial arrhythmias, in: The Atrium in Health and Disease, P. Attuel, P. Coumel, M. Janse (editors), 1989, pp. 1959–200.
• 34N. Boccara.
  
  Modeling Complex Systems, Springer, New-York Dordrecht Heidelberg London, 2010.
• 35G. Boffetta, M. Cencini, M. Falcioni, A. Vulpiani.
  
  Predictability: a way to characterize complexity, in: Physics Report, 2002, vol. 356, pp. 367–474, arXiv:nlin/0101029v1.
  
  http://dx.doi.org/10.1016/S0370-1573(01)00025-4
• 36N. Brodu.
  
  Reconstruction of epsilon-machines in predictive frameworks and decisional states, in: Advances in Complex Systems, 2011, vol. 14, n^o 05, pp. 761–794.
• 37N. Brodu, H. Yahia.
  
  Stochastic Texture Difference for Scale-Dependent Data Analysis, in: arXiv preprint arXiv:1503.03278, 2015.
• 38P. Castiglione, M. Falcioni, A. Lesne, A. Vulpiani.
  
  Chaos and coarse graining in statistical mechanics, Cambridge University Press Cambridge, 2008.
• 39M. Costa, A. L. Goldberger, C.-K. Peng.
  
  Multiscale entropy analysis of complex physiologic time series, in: Physical review letters, 2002, vol. 89, n^o 6, 068102 p.
• 40P. Coumel.
  
  Paroxysmal Atrial Fibrillation: A Disorder of Autonomic Tone ?, in: Eur. Heart J., 1994, vol. 15, n^o Supp. A, pp. 9–16.
• 41P. Coumel, et al..
  
  The atrial arrhythmia syndrome of vagal origin, in: Arch. Mal. Coeur. Vaiss., 1978, vol. 71, n^o 6, pp. 645–656.
• 42J. P. Crutchfield.
  
  Between order and chaos, in: Nature Physics, 2012, vol. 8, n^o 1, pp. 17–24.
• 43J. P. Crutchfield, K. Young.
  
  Inferring statistical complexity, in: Physical Review Letters, 1989, vol. 63, n^o 2, 105 p.
• 44G. Falasco, G. Saggiorato, A. Vulpiani.
  
  About the role of chaos and coarse graining in statistical mechanics, in: Physica A: Statistical Mechanics and its Applications, 2015, vol. 418, pp. 94–104.
• 45D. P. Feldman, J. P. Crutchfield.
  
  Measures of statistical complexity: Why?, in: Physics Letters A, 1998, vol. 238, n^o 4-5, pp. 244–252.
• 46P. Flandrin.
  
  Time-frequency/time-scale analysis, Academic press, 1998, vol. 10.
• 47G. Goerg, C. Shalizi.
  
  Mixed LICORS: A nonparametric algorithm for predictive state reconstruction, in: Artificial Intelligence and Statistics, 2013, pp. 289–297.
• 48R. M. Gray.
  
  Entropy and information theory, Springer Science & Business Media, 2011.
• 49M. Haïssaguerre, et al..
  
  Spontaneous initiation of atrial fibrillation by ectopic beats originating in the pulmonary veins, in: N. Engl. J. Med., 1998, vol. 339, n^o 10, pp. 659–666.
• 50H. Ito, L. Glass.
  
  Spiral breakup in a new model of discrete excitable media, in: Phys. Rev. Lett., 1991, vol. 66, n^o 5, pp. 671–674.
• 51P. A. Ivanov, et al..
  
  Multifractality in human heartbeat dynamics, in: Nature, 1999, vol. 399, pp. 461–465.
• 52H. Janicke, A. Wiebel, G. Scheuermann, W. Kollmann.
  
  Multifield visualization using local statistical complexity, in: IEEE Transactions on Visualization and Computer Graphics, 2007, vol. 13, n^o 6, pp. 1384–1391.
• 53J. M. Janse.
  
  Why does atrial fibrillation occur ?, in: Eur. Heart J., 1997, vol. 18, n^o Suppl. Q, pp. C12–C18.
• 54L. P. Kadanoff.
  
  Statistical physics, statics, dynamics & renormalization, World Scie,tific, 2000.
• 55A. Karma.
  
  Spiral breakup in model equations of action potential propagation in cardiac tissue, in: Phys. Rev. Lett., 1993, vol. 71, n^o 7, pp. 1103–1106.
• 56M. Martin, A. Plastino, O. Rosso.
  
  Generalized statistical complexity measures: Geometrical and analytical properties, in: Physica A: Statistical Mechanics and its Applications, 2006, vol. 369, n^o 2, pp. 439–462.
• 57A. R. Misier, et al..
  
  Increased dispersion of ’refractoriness’ in patients with idiopathic paroxysmal atrial fibrillation, in: J. Am. Coll. Cardiol., 1992, vol. 19, pp. 1531–1535.
• 58G. Moe, J. A. Abildskov.
  
  Atrial fibrillation as a self-sustaining arrhythmia independent of focal discharge, in: Am. Heart J., 1959, vol. 58, n^o 1, pp. 59–70.
• 59G. Moe, W. Rheinboldt, J. A. Abildskov.
  
  A computer model of atrial fibrillation, in: Am. Heart J., 1964, vol. 67, n^o 2, pp. 200–220.
• 60J. Nadal, P. E. Grassberger.
  
  From Statistical Physics to Statistical Inference and Back, Springer, New York Heidelberg Berlin, 1994.
  
  http://www.springer.com/physics/complexity/book/978-0-7923-2775-2
• 61P. Rensma, et al..
  
  Length of excitation wave and susceptibility to reentrant atrial arrhythmias in normal conscious dogs, in: Circ. Res., 1988, vol. 62, n^o 2, pp. 395–408.
• 62C. R. Shalizi, K. L. Shalizi.
  
  Blind construction of optimal nonlinear recursive predictors for discrete sequences, in: Proceedings of the 20th conference on Uncertainty in artificial intelligence, AUAI Press, 2004, pp. 504–511.
• 63J. Smeets, et al..
  
  The wavelength of the cardiac impulse and reentrant arrhythmias in isolated rabbit atrium. The role of heart rate, autonomic transmitters, temperature, and potassium, in: Circ. Res., 1986, vol. 1, pp. 96–108.
• 64J. L. Starck, F. Murthag, J. Fadili.
  
  Sparse Image and Signal Processing: Wavelets, Curvelets, Morphological Diversity, Cambridge University Press, 2010, ISBN:9780521119139.
• 65A. Tan, et al..
  
  Autonomic nerves in pulmonary veins, in: Heart Rythm, 2007, vol. 4, n^o Suppl. 3, pp. S57–S60.
• 66J. Ulphani, et al..
  
  The ligament of Marshall as a parasympathetic conduit, in: Am. J. Physiol. Heart Circ. Physiol., 2007, vol. 293, n^o 3, pp. H1629–H1635.
• 67V. Venugopal, et al..
  
  Revisting multifractality of high resolution temporal rainfall using a wavelet-based formalism, in: Water Resources Research, 2006, vol. 42.
• 68M. Wijffels, et al..
  
  Atrial fibrillation begets atrial fibrillation. A study in awake chronically instrumented goats, in: Circulation, 1995, vol. 92, n^o 7, pp. 1954–1968.