Distance entre les deux clusters principaux

A.5 Distance entre les deux clusters principaux

Figure A.15 – Distance entre les deux clusters principaux - 0.5, 1, 2, 5, 10 TeV et toutes énergies confondues.

Bibliographie

Actel. URL www.actel.com.

F.A. Aharonian and the HESS Collaboration. A new population of very high energy gamma-ray sources in the milky way. Science, 307 :1938–1942, 2005. URL http://xxx.lanl.gov/abs/ astro-ph/0504380.

H.H. Aiken. Proposed automatic calculating machine. IEEE Spectrum, 1 :62–69, August 1964. memorandum written 1937.

Altera. URL www.altera.com.

P. Baillon, L. Behr, S. Danagulyan, A. Djannati-Atai, B. Dudelzak, P. Espigat, P.T. Eschstruth, B. Fabre, G. Fontaine, R. George, C. Ghesquière, F. Kovács, C. Meynadier, Y. Pons, R. Ris-kalla, M. Rivoal, P. Roy, P. Schune, and J Touchard, A.M .and Vrana. Status report on themistocle experiment. In International Workshop, Towards a Major Atmospheric Cheren-kov Detector - II For TeV Astroparticle Physics , Calgary : Canada. CERN Document Ser-ver [http ://cdsweb.cern.ch/oai2d] (Switzerland), July 1993. URL http://preprints.cern.ch/ cgi-bin/setlink?base=preprint&categ=CM-P&id=CM-P00063313.

C. Baixeras, D. Bastieri, C. Bigongiari, O. Blanch, G. Blanchot, R. Bock, T. Bretz, A. Chilinga-rian, J.A. Coarasa, E. Colombo, J.C. Contreras, D. Corti, J. Cortina, C. Domingo, E. Domingo, D. Ferenc, E. Fernandez, J. Flix, V. Fonseca, L. Font, N. Galante, M. Gaug, M. Garczarczyk, J. Gebauer, M. Giller, F. Goebel, T. Hengstebeck, P. Jacone, O.C. de Jager, O Kalekin, M. Kestel, T. Kneiske, A. Laille, M Lopez, J. Lopez, E. Lorenz, K. Mannheim, M. Mariotti, M. Martinez, K. Mase, M. Merck, M. Meucci, L. Miralles, R Mirzoyan, A. Moralejo, E. Ona Willhelmi, R. Or-duna, D Paneque, R. Paoletti, D. Pascoli, N. Pavel, R. Regna, L Peruzzo, A. Piccioli, A. Roberts, R. Reyes, A. Saggion, A. Sanchez, P. Sartori, V. Scalzotto, T. Schweizer, A. Sillanpaa, D. Sobc-zynska, A. Stamerra, A. Stepanian, R. Stiehler, L. Takalo, M. Teshima, N. Tonello, A. Torres, N. Turini, V. Vitale, S. Volkov, R.M. Wagner, T. Wibig, and W. Wittek. Commissioning and first tests of the magic telescope. Nuclear Instruments and Methods in Physics Research, A518 : 188–191, 2004.

A. Barrau, R. Bazer-Bachi, E. Beyer, H. Cabot, M. Cerutti, L.M. Chounet, G. Debiais, B. Degrange, H. Delchini, J.P. Denance, G. Descotes, J.P. Dezalay, A. Djannati-Atai, D. Dumora, P. Espigat, B. Fabre, P. Fleury, G. Fontaine, R. George, C. Ghesquiere, J. Gilly, P. Goret, C. Gouiffes, J.C. Gouillaud, C. Gregory, I.A. Grenier, L. Iacoucci, L. Kalt, S. Le Bohec, I. Malet, C. Meynadier, J.P. Mols, P. Mora de Freitas, R. Morano, G. Morinaud, F. Munz, M. Palatka, T.A. Palfrey, E. Pare, Y. Pons, M. Punch, J. Quebert, K. Ragan, C. Renault, M. Rivoal, L. Rob, P. Schovanek, D. Smith, A. Tabary, J.P. Tavernet, F. Toussenel, and J. Vrana. The cat imaging telescope for very-high-energy gamma-ray astronomy. Nuclear Instruments and Methods in Physics Research, A416 :278–292, 1998.

T. Bayes. An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53 :370–418, 1763.

T. Bayes. Studies in the history of probability and statistics : Ix. thomas bayes’s essay towards solving a problem in the doctrine of chances (bayes’s essay in modernized notation). Biometrika, 45 :296–315, 1958-1763.

S.O. Belkasim, M. Ahmadi, and M. Shridhar. Efficient algorithm for fast computation of zernike moments. Journal of Franklin Institue, 333(4) :577–581, January 1996.

R.E. Bellman. Adaptive Control Processes. Princeton University Press, 1961.

D. Biggs, B. DeVille, and E. Suen. A method of choosing multiway partitions for classification and decision trees. Journal of Applied Statistics, 18(1) :49–62, January 1991.

L. Breiman, J. H. Friedman, R. A. Olshen, and C. J. Stone. Classification and Regression Trees. Wadsworth International Group, Belmont, CA, USA, 1984.

P.A. Cherenkov. Visible radiation produced by electrons moving in a medium with velocities excee-ding that of light. Physical Review, 52 :378–379, 1937. URL http://prola.aps.org/abstract/ PR/v52/i4/p378_1.

CM1K. URL http://www.general-vision.com/product_CM1K.htm.

A.H. Compton. A quantum theory of the scattering of x-rays by light elements. Physical Review, 21 :483–502, 1923. URL http://www.aip.org/history/gap/Compton/Compton.html.

M. De Naurois. L’Expérience CELESTE : Reconversion D’Une Centrale Solaire Pour L’Astronomie Gamma. Première Observation De La Nébuleuse Du Crabe Et Du Blazar Markarian 421 Entre 30 Et 300 GeV. PhD thesis, Université de Paris VI, May 2000.

B. Denby. Neural networks in high energy physics : A ten year perspective. Computer Physics Communications, 119(2) :219–231, 1999.

T.G. Dietterich and G. Bakiri. Solving multiclass learning problems via error-correcting output codes. Journal of Artificial Intelligence Research, 2 :263–286, 1995.

F.R. Elder, A.M. Gurewitsch, R.V. Langmuir, and H.C. Pollock. Radiation from electrons in a synchrotron. Physical Review, 71(6) :829–830, June 1947. URL http://adsabs.harvard.edu/ abs/1947PhRv...71..829E.

Fermi. URL http://fermi.gsfc.nasa.gov/.

J.A. Fisher. Very long instruction word architectures and the eli-512. In Proceedings of the 10th annual international symposium on Computer architecture, pages 140–150, Stockholm, Sweden, 1983. ACM.

M. J. Flynn. Some computer organizations and their effectiveness. IEEE Transactions on Compu-ters, C-21 :948–960, 1972.

P. Goret, I. Grenier, N. Petrou, A. Raviart, A. Tabary, J.L. Atteia, and R. Bazer-Bachi. Asgat : A fast timing vhe gamma-ray telescope. In Proceedings of the 22nd International Cosmic Ray Conference, volume 2, pages 630–633, August 1991.

P. Gosselin. Méthodes d’Apprentissage pour la Recherche de Catégories dans des Bases d’Images. PhD thesis, Université de Cergy-Pontoise, 2005.

B. Granado. Architecture Des Systèmes Électroniques Pour Les Réseaux De Neurones - Conception D’Une Rétine Connexionniste. PhD thesis, Université de Paris Sud, 1998.

Bibliographie

D. Hammerstrom. An Introduction To Neural And Electronic Networks, chapter 17 A Digital VLSI Architecture For Real-World Applications, pages 335–358. Academic Press, 1995.

T. Hara and the CANGAROO Group. 3.8m imaging cherenkov telescope for the tev gamma-ray astronomy collaboration between japan and australia. Nuclear Instruments and Methods in Physics Research, A332 :300–309, 1993.

M. Hatamian. A real-time two-diensional moment generating algorithm and its single chip imple-mentation. IEEE Transactions on Acoustics, Speech and Signal Processing, 34 :546–553, 1986. S. Haykin. Neural Networks : A Comprehensive Foundation. Prentice Hall, 1998.

D. Heck, J. Knapp, J.N. Capdevielle, G. Schatz, and T. Thouw. Corsika : A monte carlo code to simulate extensive air showers. Technical Report FZKA 6019, Forschungszentrum Karlsruhe, 1998.

HESS. URL http://www.mpi-hd.mpg.de/hfm/HESS/.

A.M. Hillas. Cerenkov light images of eas produced by primary gamma rays and by nuclei. In Proceeding of 19th International Cosmic Ray Conference, page 445, San Diego, California, August 1985.

J. Holder, R.W. Atkins, H.M. Badran, G. Blaylock, S.M. Bradbury, J.H. Buckley, K.L. Byrum, D.A. Carter-Lewis, O. Celik, Y.C.K. Chow, P. Cogan, W. Cui, M.K. Daniel, I. de la Calle Perez, C. Dowdall, P. Dowkontt, C. Duke, A.D. Falcone, S.J. Fegan, J.P. Finley, P. Fortin, L.F. Fortson, K. Gibbs, G. Gillanders, O.J. Glidewell, J. Grube, K.J. Gutierrez, G. Gyuk, J. Hall, D. Hanna, E. Hays, D. Horan, S.B. Hughes, T.B. Humensky, A. Imran, I. Jung, P. Kaaret, G.E. Kenny, D. Kieda, J. Kildea, J. Knapp, H. Krawczynski, F. Krennrich, M.J. Lang, S. LeBohec, E. Linton, E.K. Little, G. Maier, H. Manseri, A. Milovanovic, P. Moriarty, R. Mukherjee, P.A. Ogden, R.A. Ong, J.S. Perkins, F. Pizlo, M. Pohl, J. Quinn, K. Ragan, P.T. Reynolds, E.T. Roache, H.J. Rose, M. Schroedter, G. Sembroski, G.H. Sleege, D. Steele, S.P. Swordy, A. Syson, J.A. Toner, L. Valcarcel, V.V. Vassiliev, S.P. Wakely, T.C. Weekes, R.J. White, D.A. Williams, and R. Wagner. The first veritas telescope. Astroparticle Physics, 25(6) :391–401, July 2006.

M.-K. Hu. Visual pattern recognition by moment invariants. IRE Transactions on Information Theory, 8 :179–187, 1962.

W.M. Johnson. Superscalar Microprocessor Design. Prentice-Hall, 1991.

G.V. Kass. An exploratory technique for investigating large quantities of categorical data. 29 :. Applied Statistics, 29 :119–131, 1980.

E.C. Kintner. On the mathematical properties of the zernike polynomials. Journal of Modern Optics, 23 :679–680, 1976.

T. Kohonen. Self-Organizing Maps, volume 30 of Springer Series in Information Sciences. Springer-Verlag, Berlin, 3 rd edition, 2001.

L. Kotoulas and I. Andreadis. Real-time computation of zernike moments. IEEE Transactions On Circuits And Systems For Video Technology, 15(6) :801–809, June 2005.

D.J. Kuck. The Structure Of Computers And Computations, volume 1. John Wiley & Sons, Inc., New York, 1978.

LatticeSemiconductor. URL www.latticesemi.com.

Y. Le Cun. Une procédure d’apprentissage pour réseau à seuil asymétrique. In in proceedings of Cognitiva 85, Paris, France, June 1985.

N. Leroy. Observations avec les Télescopes H.E.S.S. du Rayonnement Gamma Émis par le Noyau Actif de Galaxie PKS 2155-304, au-delà de 100 GeV. PhD thesis, École Polytechnique, June 2004.

D. A. Lewis. Optical characteristics of the whipple observatory tev gamma-ray imaging telescope. Experimental Astronomy, 1(4) :213–226, 1990.

Y. Linde, A. Buzo, and R. Gray. An algorithm for vector quantizer design. IEEE Transactions on Communications, 28(1) :84–95, January 1980.

W.Y. Loh and Y.S. Shih. Split selection methods for classification trees. Statistica Sinica, 7 : 815–840, 1997.

S.G. Mallat. A theory for multiresolution signal decomposition : the wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7) :674–693, 1989.

J. Mercer. Functions of positive and negative type and their connection with the theory of integral equations. Philosophical Transactions of the Royal Society of London, 209, 1909.

M.L. Minsky and S.A. Papert. Perceptrons : Expanded Edition. MIT Press, Cambridge, MA, USA, 1988.

R. Mirzoyan, R. Kankanian, F. Krennrich, N. Mller, H. Sander, P. Sawallisch, F. Aharonian, A. Akhperjanian, A. Beglarian, J. Fernandez, V. Fonseca, W. Grewe, A. Heusler, A.K. Konopelko, E. Lorenz, M. Merck, A.V. Plyasheshnikov, D. Renker, M. Samorski, K. Sauerland, E. Smarsch, W. Stamm, M. Ulrich, C.A. Wiedner, and H. Wirth. The first telescope of the hegra air cherenkov imaging telescope array. Nuclear Instruments and Methods in Physics Research, A351(2-3) :513– 526, 1994.

M. Mori and the CANGAROO Group. The cangaroo-iii project. In AIP Conference Proceedings, volume 515, pages 485–491, August 1999.

R. Mukundan and K.R. Ramakrishnan. Moment Functions In Image Analysis : Theory And Appli-cations. World Scientific, Singapour, 1998.

P. Nayman. électronique pour hess-ii. may 2006.

A.R. Omondi and J.C. Rajapakse. FPGA Implementations of Neural Networks. Springer-Verlag, Dordrecht, The Netherlands, 2006.

S. Oser, D. Bhattacharya, L.M. Boone, M.C. Chantell, Z. Conner, C.E. Covault, M. Dragovan, P. Fortin, D.T. Gregorich, D.S. Hanna, R. Mukherjee, R.A. Ong, K. Ragan, R.A. Scalzo, D.R. Schuette, C.G. Théoret, T.O. Tmer, D.A. Williams, and J.A. Zweerink. High-energy gamma-ray observations of the crab nebula and pulsar with the solar tower atmospheric cerenkov effect experiment. Astrophysical Journal, 547 :949–958, February 2001.

M.J.D. Powell. Algorithms for Approximation, chapter Radial basis functions for multivariate in-terpolation : a review, pages 143–167. Oxford, 1987.

J.-C. Prévotet. Étude Des Systèmes Électroniques Pour Les Réseaux Connexionnistes Appliqués À L’Instrumentation En Temps-Réel. PhD thesis, Université de Paris VI - Pierre et Marie Curie, 2002.

U. Ramacher. Synapse - a neurocomputer that synthesizes neural algorithms on a parallel systolic engine. Journal of Parallel and Distributed Computing, 14(3) :306–318, March 1992.

F. Rosenblatt. The perceptron : a probabilistic model for information storage and organization in the brain. Psychological Review, 65(6) :386–408, November 1958.

Bibliographie

D.E. Rumelhart, G.E. Hinton, and R.J. Williams. Parallel Distributed Processing : Explorations In The Microstructure Of Cognition, chapter 8 Learning Internal Representations By Error Back-propagation, pages 318–362. MIT PRESS, 1986a.

D.E. Rumelhart, J.L. McClelland, and PDP Research Group. Parallel Distributed Processing : Explorations In The Microstructure Of Cognition. MIT Press, Cambridge , MA, USA, 1986b. B.R. Santo. 25 microchips that shook the world. IEEE Spectrum, 46(5) :34–43, May 2009.

S.M. Stigler. Thomas bayes’ bayesian inference. Journal of the Royal Statistical Society, Series A, 145 :250–258, 1982.

B.N. Swanenburg, K. Bennett, G.F. Bignami, R. Buccheri, P. Caraveo, W. Hermsen, G. Kanbach, G.G. Lichti, J.L. Masnou, H.A. Mayer-Hasselwander, J.A. Paul, B. Sacco, L. Scarsi, and R.D. Wills. Second cos b catalog of high-energy gamma-ray sources. Astrophysical Journal, 243 :69–73, 1981.

T. Tanimori and the CANGAROO Group. Construction of new 7m imaging air Čerenkov telescope of cangaroo. In Proceedings of the 26th International Cosmic Ray Conference, volume 5, pages 203–306, August 1999.

M.R. Teague. Image analysis via the general theory of moments. Journal of the Optical Society of America, 70(8) :920–930, August 1980.

P.C. Treleaven, D.R. Brownbridge, and R.P. Hopkins. Data-driven and demand-driven computer architecture. ACM Computing Surveys, 14(1) :93–143, 1982.

V.N. Vapnik. The Nature Of Statistical Learning Theory. Springer-Verlag, New York, USA, 1995. J. Von Neumann. The first draft report on the edvac, June 1945.

J.H. Ward. Hierarchical grouping to optimise an objective function. Journal of the American Statistical Association, 58 :238–244, 1963.

P.J. Werbos. Beyond Regression : New Tools for Prediction and Analysis in the Behavioral Sciences. PhD thesis, Harvard University, Cambridge, MA, USA, 1974.

Xilinx. URL www.xilinx.com.

F. Zernike. Beugungstheorie des schneidenverfahrens und seiner verbesserten form, der phasenkon-trastmethode. Physica, 1 :689–704, 1934.

L’expérience HESS consiste en un système de télescopes permettant d’observer les rayonne-ments cosmiques. Compte tenu des résultats majeurs obtenus depuis son installation, la seconde phase du projet a été engagée. Celle-ci est en cours de réalisation et passe par l’ajout d’un télescope plus sensible et plus grand que ses prédécesseurs. Toutes les données collectées par ce télescope ne peuvent pas être conservées à cause des limites de stockage. Par conséquent, un système de déclencheur, dit trigger, performant doit être mis en place.

L’objectif de cette thèse est de proposer une solution de reconnaissance de formes en temps réel dans un contexte fortement contraint et qui sera embarquée sur le télescope. La première partie de la thèse a consisté à élaborer une chaine de reconnaissance des formes pour ce trigger. Une chaine de traitement à base de réseau de neurones et des moments de Zernike a été validée. La seconde partie de la thèse a porté sur l’implantation des algorithmes retenus sur une cible FPGA en tenant compte des contraintes en termes de ressources et de temps d’exécution.

Abstract

The HESS experiment consists of a system of telescopes destined to observe cosmic rays. Since the project has achieved a high level of performances, a second phase of the project has been initiated. This implies the addition of a new telescope which is more sensitive than its predecessors and which is capable of collecting a huge amount of images. In this context, all data collected by the telescope can not be retained because of storage limitations. Therefore, a new real-time system trigger must be designed in order to select interesting events on the fly.

The purpose of this thesis was to propose a trigger solution to efficiently discriminate events (images) which are captured by the telescope.The first part of this thesis was to develop pattern recognition algorithms to be implemented within the trigger. A processing chain based on neural networks and Zernike moments has been validated.

The second part of the thesis has focused on the implementation of the proposed algorithms onto an FPGA target, taking into account the application constraints in terms of resources and execution time.