P. Absil, R. Sepulchre, P. Bilge, and . Gérard, Nonlinear analysis of cardiac rhythm fluctuations using dfa method. Physica A : Statistical mechanics and its applications, vol.272, pp.235-244, 1999.

A. Adcock, E. Carlsson, and G. Carlsson, The ring of algebraic functions on persistence bar codes, vol.18, p.2013

. Ms-aini and . Fakhrul-razi, Development of socio-technical disaster model, Safety science, vol.48, issue.10, pp.1286-1295, 2010.

. Ni-akhiezer and . Glazman, Theory of Linear Operators in Hilbert Space, vol.1

S. Aminikhanghahi and D. J. Cook, A survey of methods for time series change point detection. Knowledge and information systems, vol.51, pp.339-367, 2017.

G. Ammar, W. Gragg, and L. Reichel, Constructing a Unitary Hessenberg Matrix from Spectral Data, Number 70 in NATO ASI Series, pp.385-395, 1991.

G. Ammar and C. Martin, The geometry of matrix eigenvalue methods, Acta Applicandae Mathematica, vol.5, issue.3, pp.239-278, 1986.

S. Gregory, W. Ammar, and . Gragg, Schur flows for orthogonal hessenberg matrices, 1993.

. Gs-ammar and . Calvetti, Continuation methods for the computation of zeros of szegö polynomials. Linear algebra and its applications, vol.249, pp.125-155, 1996.

M. Arnaudon, F. Barbaresco, and L. Yang, Riemannian medians and means with applications to radar signal processing, IEEE Journal of Selected Topics in Signal Processing, vol.7, issue.4, 2013.

I. Vladimir and . Arnold, Sur la géométrie différentielle des groupes de lie de dimension infinie et ses applicationsa l'hydrodynamique des fluides parfaits, Ann. Inst. Fourier, vol.16, issue.1, pp.319-361, 1966.

. Gr, T. Arsene, and . Constantinescu, The structure of the Naimark dilation and Gaussian stationary processes, vol.8, pp.181-204, 1985.

B. Balaji, F. Barbaresco, and A. Decurninge, Information geometry and estimation of Toeplitz covariance matrices, Int. Radar Conf, pp.1-4, 2014.

F. Barbaresco, Geometric Radar Processing based on Fréchet distance : Information geometry versus Optimal Transport Theory, 12th Int. Radar Symp, pp.663-668, 2011.

F. Barbaresco, Information Geometry of Covariance Matrix : Cartan-Siegel Homogeneous Bounded Domains, Mostow/Berger Fibration and Fréchet Median, In Matrix Inf. Geom, pp.199-255, 2013.

F. Barbaresco, Interactions between symmetric cone and information geometries : Bruhat-tits and siegel spaces models for high resolution autoregressive doppler imagery

, Emerging Trends in Visual Computing, pp.124-163, 2009.

F. Barbaresco, Geometric radar processing based on fréchet distance : information geometry versus optimal transport theory, Radar Symposium (IRS), 2011 Proceedings International, pp.663-668, 2011.

F. Barbaresco, Poly-symplectic model of higher order souriau lie groups thermodynamics for small data analytics, International Conference on Geometric Science of Information, pp.432-441, 2017.

F. Barbaresco and M. Ruiz, Radar detection for non-stationary doppler signal in one burst based on information geometry : Distance between paths on covariance matrices manifold, Radar Conference (EuRAD), pp.41-44, 2015.

M. Bauer, M. Bruveris, S. Marsland, and P. W. Michor, Constructing reparameterization invariant metrics on spaces of plane curves, Differential Geometry and its Applications, vol.34, pp.139-165, 2014.

M. Bauer, M. Bruveris, and P. W. Michor, Why Use Sobolev Metrics on the Space of Curves, Riemannian Computing in Computer Vision, pp.233-255, 2016.

M. Bauer, M. Eslitzbichler, and M. Grasmair, Landmark-guided elastic shape analysis of human character motions, 2015.

M. Bauer, M. Eslitzbichler, and M. Grasmair, Landmark-Guided Elastic Shape Analysis of Human Character Motions, 2015.

P. Bendich, E. James-s-marron, A. Miller, S. Pieloch, and . Skwerer, Persistent homology analysis of brain artery trees. The annals of applied statistics, vol.10, p.198, 2016.

. Wr and . Bennett, Statistics of regenerative digital transmission, Bell System Technical Journal, vol.37, issue.6, pp.1501-1542, 1958.

N. H. Bingham, Szegö's theorem and its probabilistic descendants, Probability Surveys, vol.9, pp.287-324, 2012.

G. Blanchet and M. Charbit, Signaux et images sous matlab, 2001.

O. Bobrowski and M. Kahle, Topology of random geometric complexes : a survey, Journal of Applied and Computational Topology, pp.1-34, 2014.

G. Bouleux, E. Marcon, and O. Mory, Early index for detection of pediatric emergency department crowding, IEEE journal of biomedical and health informatics, vol.19, issue.6, pp.1929-1936, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01359977

N. Boumal, Interpolation and regression of rotation matrices, Geometric Science of Information, pp.345-352, 2013.

T. Florence, C. Bourgeois, J. C. Valim, A. J. Wei, K. D. Mcadam et al., Influenza and other respiratory virus-related emergency department visits among young children, Pediatrics, vol.118, issue.1, pp.1-8, 2006.

A. L. Brigant, Computing distances and geodesics between manifold-valued curves in the SRV framework, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01253495

A. L. Brigant, A discrete framework to find the optimal matching between manifoldvalued curves, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01490695

P. Bubenik, Statistical Topological Data Analysis Using Persistence Landscapes, J. Mach. Learn. Res, vol.16, issue.1, pp.77-102, 2015.

J. Burg, Maximum entropy spectral analysis, 37th Annual International Meeting. Society of Exploration Geophysics, 1967.

G. Pablo, A. J. Cámara, R. Levine, and . Rabadán, Inference of ancestral recombination graphs through topological data analysis, PLoS computational biology, vol.12, issue.8, p.1005071, 2016.

G. Carlsson, T. Ishkhanov, V. D. Silva, and A. Zomorodian, On the local behavior of spaces of natural images, International journal of computer vision, vol.76, issue.1, pp.1-12, 2008.

E. Celledoni, S. Eidnes, and A. Schmeding, Shape analysis on homogeneous spaces : a generalised srvt framework, 2017.

E. Celledoni, M. Eslitzbichler, and A. Schmeding, Shape analysis on Lie groups with applications in computer animation, 2015.

G. Chiandussi, M. Codegone, S. Ferrero, and F. E. Varesio, Comparison of multi-objective optimization methodologies for engineering applications, Computers & Mathematics with Applications, vol.63, issue.5, pp.912-942, 2012.

H. Chintakunta, T. Gentimis, R. Gonzalez-diaz, M. Jimenez, and H. Krim, An entropy-based persistence barcode, Pattern Recognition, vol.48, issue.2, pp.391-401, 2015.

S. Akopovich-chobanyan and A. Weron, Banach-space-valued stationary processes and their linear prediction, 1975.

T. Constantinescu, Schur Parameters, Factorization and Dilation Problems, Birkhäuser Basel, 1995.

T. Constantinescu, On the structure of the naimark dilation, Journal of Operator Theory, pp.159-175, 1984.

T. Constantinescu, Some aspects of non-stationarity. Prepr. ser. in mathematics, 1988.

P. Coriat, . Braun, P. Genet, . Goldstein, . Nazac et al., Propositions sur la composition, les missions et le champ d'action du conseil national de l'urgence et de la permanence des soins. paris : Ministère de la santé, de la jeunesse, des sports et de la vie associative, 2008.

D. Damanik, A. Pushnitski, and B. Simon, The analytic theory of matrix orthogonal polynomials, Surveys in Approximation Theory, 4, 2008.

D. Dehay, L. Harry, A. Hurd, and . Makagon, Spectrum of periodically correlated fields, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00842839

P. Delsarte, Y. Genin, and . Kamp, Schur parametrization of positive definite blocktoeplitz systems, SIAM Journal on Applied Mathematics, vol.36, issue.1, pp.34-46, 1979.

P. Delsarte, Y. Genin, and . Kamp, Orthogonal polynomial matrices on the unit circle, IEEE Transactions on Circuits and Systems, vol.25, issue.3, pp.149-160, 1978.

W. Robert, J. Derlet, and . Richards, Overcrowding in the nation's emergency departments : complex causes and disturbing effects, Annals of emergency medicine, vol.35, issue.1, pp.63-68, 2000.

F. Desbouvries, Unitary hessenberg and state-space model based methods for the harmonic retrieval problem, IEE Proceedings-Radar, Sonar and Navigation, vol.143, issue.6, pp.346-348, 1996.

F. Desbouvries, Non-euclidean geometrical aspects of the schur and levinson-szego algorithms, IEEE Transactions on Information Theory, vol.49, issue.8, pp.1992-2003, 2003.
URL : https://hal.archives-ouvertes.fr/hal-01347779

Y. P. Dragan and . Yavorskii, The periodic correlation-random field as a model for bidimensional ocean waves, Otbor Peredacha Inform, vol.51, pp.15-21, 1982.

M. Dugast, G. Bouleux, and E. Marcon, Representation and characterization of nonstationary processes by dilation operators and induced shape space manifolds
URL : https://hal.archives-ouvertes.fr/hal-02166149

S. Dégerine and S. Lambert-lacroix, Evolutive instantaneous spectrum associated with partial autocorrelation function, 2002.

S. Dégerine and S. Lambert-lacroix, Characterization of the partial autocorrelation function of nonstationary time series, Journal of Multivariate Analysis, vol.87, issue.1, pp.46-59, 2003.

H. Edelsbrunner, D. Letscher, and A. Zomorodian, Topological persistence and simplification, Foundations of Computer Science, 2000. Proceedings. 41st Annual Symposium on, pp.454-463, 2000.

H. Edelsbrunner and D. Morozov, Persistent Homology : Theory and Practice

F. Elvander, A. Jakobsson, and J. Karlsson, Using optimal mass transport for tracking and interpolation of toeplitz covariance matrices, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.4469-4473, 2018.

G. S-a-emine, H. Bouleux, E. Haouba, and . Marcon, Emergency Department Overcrowding Detection by a Multifractal Analysis, 10th IFAC Symposium on Biological and Medical Systems (IFACBMS 2018), 2018.

. Bibliographie,

C. Foias and A. E. Frazho, A geometric approach to positive definite sequences, The Commutant Lifting Approach to Interpolation Problems, number 44 in OT44 Operator Theory : Advances and Applications, pp.497-546, 1990.

C. Foias, A. E. Frazho, and P. J. Sherman, A geometric approach to the maximum likelihood spectral estimator for sinusoids in noise, IEEE Transactions on Information Theory, vol.34, issue.5, pp.1066-1070, 1988.

C. Foias, A. E. Frazho, and P. J. Sherman, A new approach for determining the spectral data of multichannel harmonic signals in noise, Mathematics of Control, Signals and Systems, vol.3, issue.1, pp.31-43, 1990.

A. E. Frazho, On Stochastic Bilinear Systems, Modelling and Application of Stochastic Processes, pp.215-241, 1986.

A. William and . Gardner, Statistical spectral analysis : a nonprobabilistic theory, 1986.

A. William, A. Gardner, L. Napolitano, and . Paura, Cyclostationarity : Half a century of research, Signal processing, vol.86, issue.4, pp.639-697, 2006.

. Ia-l-geronimus, , vol.18, 1960.

B. Georgios and . Giannakis, Cyclostationary signal analysis, Digital Signal Processing Handbook, pp.17-18, 1998.

N. Giansiracusa, R. Giansiracusa, and C. Moon, Persistent homology machine learning for fingerprint classification, 2017.

C. Giusti, E. Pastalkova, C. Curto, and V. Itskov, Clique topology reveals intrinsic geometric structure in neural correlations, Proceedings of the National Academy of Sciences, vol.112, issue.44, pp.13455-13460, 2015.

. Eg-gladyshev, Periodically correlated random sequences, Doklady Akademii Nauk, vol.137, pp.1026-1029, 1961.

G. Agnieszka-kitlas, Detrended fluctuation analysis (dfa) in biomedical signal processing : selected examples. Stud. Logic Grammar Rhetoric, vol.29, pp.107-115, 2012.

H. Gene, C. Golub, and . Loan, Matrix computations, vol.3, 2012.

J. Górniak and . Weron, Aronszajn-kolmogorov type theorems for positive definite kernels in locally convex spaces, Studia Math, vol.69, issue.3, pp.235-246, 1980.

B. William and . Gragg, The qr algorithm for unitary hessenberg matrices, Journal of Computational and Applied Mathematics, vol.16, issue.1, pp.1-8, 1986.

B. William and . Gragg, Positive definite toeplitz matrices, the arnoldi process for isometric operators, and gaussian quadrature on the unit circle, Journal of Computational and Applied Mathematics, vol.46, issue.1-2, pp.183-198, 1993.

. Pr-halmos, Introduction to hilbert space and the theory of spectral multiplicity, vol.13, p.512, 1951.

K. Hasselmann and . Barnett, Techniques of linear prediction for systems with periodic statistics, Journal of the Atmospheric Sciences, vol.38, issue.10, pp.2275-2283, 1981.

C. Hofer, R. Kwitt, M. Niethammer, and A. Uhl, Deep learning with topological signatures, Advances in Neural Information Processing Systems, pp.1634-1644, 2017.

M. Hofer and H. Pottmann, Energy-minimizing splines in manifolds, ACM Transactions on Graphics (TOG), vol.23, issue.3, pp.284-293, 2004.

N. R. Hoot, S. K. Epstein, T. L. Allen, S. S. Jones, K. M. Baumlin et al.,

D. Gadd and . Aronsky, Forecasting emergency department crowding : an external, multicenter evaluation, Annals of Emergency Medicine, vol.54, issue.4, pp.514-522, 2009.

H. L. Hurd and A. Miamee, Periodically Correlated Random Sequences : Spectral Theory and Practice, Wiley Series in Probability and Statistics, 2007.

V. Isham, Assessing the variability of stochastic epidemics, Mathematical biosciences, vol.107, issue.2, pp.209-224, 1991.

S. Spencer, T. L. Jones, T. J. Allen, S. J. Flottemesch, and . Welch, An independent evaluation of four quantitative emergency department crowding scales, Academic Emergency Medicine : Official Journal of the Society for Academic Emergency Medicine, vol.13, issue.11, pp.1204-1211, 2006.

F. Kadri, Contribution à la conception d'un système d'aide à la décision pour la gestion de situations de tension au sein des systèmes hospitaliers. Application à un service d'urgence, 2014.

T. Kailath, Time-Variant and Time-Invariant Lattice Filters for Nonstationary Processes, DTIC Document, 1982.

T. Kailath and A. M. Bruckstein, Naimark Dilations, State-Space Generators and Transmission Lines, Number 17 in Operator Theory : Advances and Applications, pp.173-186

B. Basel, , 1986.

I. G. Kang and . Park, Cubic spline algorithms for orientation interpolation, International journal for numerical methods in engineering, vol.46, issue.1, pp.45-64, 1999.

L. Krishan, . Khatri, S. Lakshman, and . Tamil, Early detection of peak demand days of chronic respiratory diseases emergency department visits using artificial neural networks, IEEE journal of biomedical and health informatics, vol.22, issue.1, pp.285-290, 2018.

S. Kobayashi and K. Nomizu, Foundations of differential geometry, Interscience publishers, vol.1, 1963.

A. Kolker, Process Modeling of Emergency Department Patient Flow : Effect of Patient Length of Stay on ED Diversion, Journal of Medical Systems, vol.32, issue.5, pp.389-401, 2008.

A. Kriegl, W. Peter, and . Michor, Aspects of the theory of infinite dimensional manifolds, Differential Geometry and its Applications, vol.1, issue.2, pp.159-176, 1991.

S. Lambert, Sur l'estimation autorégressive des processus périodiquement corrélés

, Colloque sur le traitement du signal et des images, FRA, 1997. GRETSI, Groupe d'Etudes du Traitement du Signal et des Images, 1997.

S. Lambert-lacroix, Extension of Autocovariance Coefficients Sequence for Periodically Correlated Processes, Journal of Time Series Analysis, vol.26, issue.3, pp.423-435, 2005.

M. Laskowski, R. D. Mcleod, M. R. Friesen, B. W. Podaima, and S. Attahiru,

A. , Models of Emergency Departments for Reducing Patient Waiting Times, PLOS ONE, vol.4, issue.7, p.6127, 2009.

A. L. Brigant, M. Arnaudon, and F. Barbaresco, Optimal matching between curves in a manifold, International Conference on Geometric Science of Information, pp.57-64, 2017.

H. Lev-ari and T. Kailath, Lattice filter parameterization and modeling of nonstationary processes, IEEE Transactions on Information Theory, vol.30, issue.1, pp.2-16, 1984.

Y. Li and K. Wong, Riemannian distances for signal classification by power spectral density, IEEE Journal of Selected Topics in Signal Processing, vol.7, issue.4, pp.655-669, 2013.

K. Lii and M. Rosenblatt, Estimation for almost periodic processes, The Annals of Statistics, vol.34, issue.3, pp.1115-1139, 2006.

C. Robert and . Lloyd, Quality health care : a guide to developing and using indicators, 2004.

A. Makagon and H. Salehi, Notes on infinite dimensional stationary sequences, Probability Theory on Vector Spaces IV, pp.200-238, 1989.

A. Makagon and A. Miamee, Spectral representation of periodically correlated sequences, Probab. Math. Statist, vol.33, issue.1, pp.175-188, 2013.

P. Masani, Dilations as Propagators of Hilbertian Varieties, SIAM J. Math. Anal, vol.9, issue.3, pp.414-456, 1978.

A. Acg-mennucci, G. Yezzi, and . Sundaramoorthi, Sobolev-type metrics in the space of curves, Interfaces and Free Boundaries, vol.10, issue.4, pp.423-445, 2008.

W. Peter and . Michor, Manifolds of differentiable mappings, vol.3, 1980.

W. Peter and . Michor, Topics in differential geometry, vol.93, 2008.

W. Peter, D. Michor, and . Mumford, Vanishing geodesic distance on spaces of submanifolds and diffeomorphisms, Doc. Math, vol.10, pp.217-245, 2005.

W. Peter, D. Michor, and . Mumford, An overview of the riemannian metrics on spaces of curves using the hamiltonian approach, Applied and Computational Harmonic Analysis, vol.23, issue.1, pp.74-113, 2007.

F. Nielsen and R. Bhatia, Matrix information geometry, 2013.

S. Othman and . Hammadi, Driven workflow orchestration of patient pathway in hospital emergencies, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01724166

N. Otter, A. Mason, U. Porter, P. Tillmann, H. A. Grindrod et al., A roadmap for the computation of persistent homology, EPJ Data Science, vol.6, issue.1, p.17, 2017.

E. Parzen and M. Pagano, An approach to modeling seasonally stationary time series, Journal of Econometrics, vol.9, issue.1-2, pp.137-153, 1979.

R. Payen, Fonctions aléatoires du second ordre à valeurs dans un espace de hilbert

A. Inst and . Henri-poincare, , vol.3, pp.323-396, 1967.

X. Pennec, Probabilities and statistics on riemannian manifolds : A geometric approach, INRIA, 2004.
URL : https://hal.archives-ouvertes.fr/inria-00071490

X. Pennec, Intrinsic statistics on Riemannian manifolds : Basic tools for geometric measurements, Journal of Mathematical Imaging and Vision, vol.25, issue.1, pp.127-154, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00614994

X. Pennec, P. Fillard, and N. Ayache, A Riemannian framework for tensor computing, International Journal of Computer Vision, vol.66, issue.1, pp.41-66, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00070743

A. Jose, J. Perea, and . Harer, Sliding windows and persistence : An application of topological methods to signal analysis, Foundations of Computational Mathematics, vol.15, issue.3, pp.799-838, 2015.

M. M. Cássio, R. Pereira, and . Mello, Persistent homology for time series and spatial data clustering, Expert Systems with Applications, vol.42, pp.6026-6038, 2015.

M. Piangerelli, M. Rucco, L. Tesei, and E. Merelli, Topological classifier for detecting the emergence of epileptic seizures, BMC research notes, vol.11, issue.1, p.392, 2018.

M. Pilté and F. Barbaresco, Tracking quality monitoring based on information geometry and geodesic shooting, Radar Symposium (IRS), pp.1-6, 2016.

A. Port, I. Gheorghita, D. Guth, M. John, C. Clark et al., Persistent topology of syntax. Mathematics in Computer Science, vol.12, issue.1, pp.33-50, 2018.

P. Lloyd, S. K. Provost, and . Murray, The data guide : learning from data to improve health care, Process Improvement and Corporate Transformation Concepts, 2010.

M. Rucco, F. Castiglione, E. Merelli, and M. Pettini, Characterisation of the Idiotypic Immune Network Through Persistent Entropy, Proceedings of ECCS 2014, pp.117-128, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01260143

A. H. Sayed, T. Constantinescu, and T. Kailath, Recursive Construction of Multichannel Transmission Lines with a Maximum Entropy Property, Codes, Graphs, and Systems, pp.259-290, 2002.

. Schur, On power series which are bounded in the interior of the unit circle i and ii, vol.148, pp.122-145, 1918.

T. Shingel, Interpolation in special orthogonal groups, IMA journal of numerical analysis, vol.29, issue.3, pp.731-745, 2008.

B. Simon, CMV matrices : Five years after, Journal of Computational and Applied Mathematics, vol.208, issue.1, pp.120-154, 2007.

B. Simon, Orthogonal Polynomials on the Unit Circle Part1 and Part 2, vol.54, 2009.

G. Soler, G. Bouleux, E. Marcon, A. Cantais, S. Pillet et al., Emergency department admissions overflow modeling by a clustering of time evolving clinical diagnoses, 14th IEEE International Conference on Automation Science and Engineering, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01885975

A. Srivastava, E. Klassen, S. H. Joshi, and I. H. Jermyn, Shape Analysis of Elastic Curves in Euclidean Spaces, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, issue.7, pp.1415-1428, 2011.

Z. Su, E. Klassen, and M. Bauer, Comparing Curves in Homogeneous Spaces, 2017.

B. Sz, C. Nagy, H. Foias, L. Bercovici, and . Kérchy, Harmonic Analysis of Operators on Hilbert Space, 2010.

G. Szegö, Orthogonal Polynomials, 1959.

H. Takai and H. Yamada, A note on the dilation theorems, Proceedings of the Japan Academy, vol.48, issue.4, pp.216-220, 1972.

H. Takai and H. Yamada, A note on the dilation theorems, Proceedings of the Japan Academy, vol.48, issue.4, pp.216-220, 1972.

D. Timotin, Prediction theory and choice sequences : an alternate approach, Advances in invariant subspaces and other results of operator theory, pp.341-352, 1986.

M. Chad, L. Topaz, T. Ziegelmeier, and . Halverson, Topological data analysis of biological aggregation models, PloS one, vol.10, issue.5, p.126383, 2015.

M. C. Tseng, Contractions, Matrix Paramatrizations, and Quantum Information, 2006.

M. C. Tseng and V. Ramakrishna, Dilation Theoretic Parametrizations of Positive Matrices with Applications to Quantum Information, 2006.

Y. Umeda, Time series classification via topological data analysis, Information and Media Technologies, vol.12, pp.228-239, 2017.

S. Verblunsky, On positive harmonic functions, Proceedings of the London Mathematical Society, vol.2, issue.1, pp.290-320, 1936.

M. Vidyasagar, Kullback-leibler divergence rate between probability distributions on sets of different cardinalities, Decision and Control (CDC), 2010 49th IEEE Conference on, pp.948-953, 2010.

A. Weron, Remarks on positive-definite operator valued functions in banach spaces, Bulletin de l'Academie Polonaise des Sciences. Serie des Sciences Chimiques, issue.10, pp.873-876, 1976.

A. Weron, Stochastic Processes of Second Order with Values in Banach Spaces. Number 7A in Transactions of the 7th Prague Conference on Information Theory, Statistical Decision Functions, Random Processes, pp.567-574, 1977.

L. Yang, M. Arnaudon, and F. Barbaresco, Riemannian median, geometry of covariance matrices and radar target detection, Radar Conference (EuRAD), pp.415-418, 2010.

H. Y. Florence, . Yap, . Pak-leung, K. Ho, P. K. Lam et al., Excess hospital admissions for pneumonia, chronic obstructive pulmonary disease, and heart failure during influenza seasons in Hong Kong, Journal of Medical Virology, vol.73, issue.4, pp.617-623, 2004.

L. Younes, Computable elastic distances between shapes, SIAM Journal on Applied Mathematics, vol.58, issue.2, pp.565-586, 1998.

G. Udny and Y. , On the theory of correlation for any number of variables, treated by a new system of notation, Proc. R. Soc. Lond. A, vol.79, pp.182-193, 1907.

Z. Zhang, J. Su, E. Klassen, H. Le, and A. Srivastava, Video-based action recognition using rate-invariant analysis of covariance trajectories, 2015.

A. Zomorodian and G. Carlsson, Computing Persistent Homology, Discrete Comput Geom, vol.33, issue.2, pp.249-274, 2005.

P. Un, ) de période 20 points pour 1000 point représenté, et sa trajectoire dans SO(3)

, 11) et le signal de la Fig. 2.7-(c) calculée à partir de l'équation 2.31. La première ligne correspond à une interpolation avec 200 points, la seconde avec 50 points

, ce qui se traduit par le fait que les deux courbes fermées rouges et bleues ne peuvent pas se transformer l'une en l'autre par transformation continue. Imaginons que ces deux courbes soient des élastiques. Nous ne pouvons pas passer de l'élastique rouge à l'élastique bleu sans le casser

, Dans la rangée du haut sont représentés succesivement un 0-simplexe, un 1-simplexe et un 2-simplexe. Dans la rangée du bas ce sont les faces de ces simplexes qui sont représentées

, de deux triangles rouges, vol.8

, Quelques étapes de la filtration de Vietoris-Rips. Un cycle se crée à la troisième étape (également à la deuxième en tant que bord du triangle). Il disparaîtra lorsque les quatre cercles centrés aux quatre sommets correspondant s'intersecteront, p.79

B. Un-cercle, Le point isolé dans le diagramme de persistance traduit l'organisation circulaire de ce nuage de points

?. Le-nombre-de-betti-au-temps-? and . Rho, En faisant varier ?, nous obtenons la séquence des nombres Betti

, La trajectoire sur le groupe SO(3) formée par les matrices de dilations de ce signal. La trajectoire est représenté à l'intérieur d'une boule unité, échantillons on été tirés, avec 20 point par périodes.(b)

, Le diagramme de persistance à l'ordre 1 du signal de la Fig. 3.7-(a)

, Une réalisation de chaque modèle utilisé dans notre classification

, 32 sequences de 10 parcors chacune ont été utilisées pour obtenir le nuage de matrice de dilation. Les diagrammes de persistance ont été obtenus avec le package Dionysus sous Python, Les diagrammes de persistance pour une réalisation de chacun des processus figurant à la Fig. 3.9

, Projection des données après une réduction de dimension à deux composantes principales, (a) Les données ne peuvent pas être différenciées avec seulement deux composantes principales. (b) Certains processus sont néanmoins bien distinguables, vol.87

, entropie persistante normalisée à l'ordre i = 0, 1 ; f i , les caractéristique polynomiales à l'ordre i, b i les caractéristique de Betti à l'odre i. Le rôle singulier de l'entropie persistante est clairement visible, Contributions des caractéristiques aux axes principaux PC1 et PC2. H i désigne l, vol.87

, Haut : un exemple du nuage de point obtenu pour chaque niveaux de bruit. Bas : les histogrammes des valeurs d'entropies persistantes correspondants

, Histogramme des valeurs de l'entropie normalisée à l'ordre 0 pour 500 réalisations par processus

, Histogramme des valeurs de l'entropie normalisée à l'ordre 1 pour 500 réalisations par processus

, Séquence de Betti moyenne obtenue après 500 réalisations pour chacun des processus

, Les points du diagramme noir sont associés aux points du diagramme rouge de sorte à ce que la somme des déplacements soit minimale

. Ici,

, (a) évolution temporelle de Bar max (k), (b) évolution temporelle de PE norm (k) pour le processus Fig.4.1. La longueur de la fenêtre glissante est N = 4. Les longueurs de la DFA sont de L = 50 et

, (b) Les dates correspondantes aux trois détections sur la période considérée pour une longueur de la DFA de L = 24, Deux critères sont minimisés : f (L), p.107

, 11-25) et estimation du nombre d'arrivée maximal (2017-01-15) obtenue avec le détecteur calibré pour l, Détection d'un nombre d'arrivées anormal, pp.2016-2017, 2016.

, Comparaison entre l'indicateur Bar max et trois autres méthode de détection de changement : une carte de contrôle, un cusum et un kurtosis local, p.109

A. ,

, Un triangle dans un espace à deux dimensions

A. ,

, Un tetraedre est un 3-simplexes. Ces faces sont des 2-simplexes ou des 1-simplexes, vol.117

A. ,

A. ,

A. ,

. Ex, 3 un cercle est homéomorphe à un triangle

A. ,

. Ex, 4 un disque est homéomorphe à un triangle. Le triangle est orienté dans le sens trigonométrique

A. ,

. Ex, Une sphère, homéomorphe à un tétraèdre. Par souci de clarté, toutes les orientations non pas été représentées

A. ,

. Ex, Un tore, qui est homéomorphe à deux triangles collés dont tous les sommets on été identifiés. Par souci de clarté, toutes les orientations non pas été représentées, p.127

, Table des figures