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Your search keyword '"Marconi S"' showing total 11 results
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11 results on '"Marconi S"'

2. Design implementation and test results of the RD53A, a 65 nm large scale chip for next generation pixel detectors at the HL-LHC

Author

Marconi, S., primary, Barbero, M. B., additional, Fougeron, D., additional, Godiot, S., additional, Menouni, M., additional, Pangaud, P., additional, Rozanov, A., additional, Breugnon, P., additional, Bomben, M., additional, Calderini, G., additional, Crescioli, F., additional, Dortz, O. Le, additional, Marchiori, G., additional, Dzahini, D., additional, Rarbi, F. E., additional, Gaglione, R., additional, Kruger, H., additional, Daas, M., additional, Dieter, Y., additional, Hemperek, T., additional, Hugging, F., additional, Moustakas, K., additional, Pohl, D., additional, Rymaszewski, P., additional, Standke, M., additional, Vogt, M., additional, Wang, T., additional, Wermes, N., additional, Karagounis, M., additional, Stiller, A., additional, Marzocca, C., additional, Marzocca, G., additional, De Robertis, G., additional, Loddo, F., additional, Licciulli, F., additional, Andreazza, A., additional, Liberali, V., additional, Stabile, A., additional, Frontini, L., additional, Bagatin, M., additional, Bisello, D., additional, Gerardin, S., additional, Mattiazzo, S., additional, Paccagnella, A., additional, Vogrig, D., additional, Bonaldo, S., additional, Bacchetta, N., additional, Gaioni, L., additional, De Canio, F., additional, Manghisoni, M., additional, Re, V., additional, Riceputi, E., additional, Traversi, G., additional, Ratti, L., additional, Vacchi, C., additional, Androsov, K., additional, Beccherle, R., additional, Magazzu, G., additional, Minuti, M., additional, Morsani, F., additional, Palla, F., additional, Poulios, S., additional, Bilei, G. M., additional, Menichelli, M., additional, Placidi, P., additional, Dellacasa, G., additional, Demaria, N., additional, Mazza, G., additional, Monteil, E., additional, Pacher, L., additional, Paterno, A., additional, Rivetti, A., additional, Da Rocha Rolo, M. D., additional, Gajanana, D., additional, Gromov, V., additional, van Eijk, B., additional, Kluit, R., additional, Vitkovskiy, A., additional, Benka, T., additional, Havranek, M., additional, Janoska, Z., additional, Marcisovsky, M., additional, Neue, G., additional, Tomasek, L., additional, Kafka, V., additional, Vrba, V., additional, Lopez-Morillo, E., additional, Palomo, F. R., additional, Munoz, F., additional, Vila, I., additional, Jimenez, E. M. S., additional, Abbaneo, D., additional, Christiansen, J., additional, Orfanelli, S., additional, Jara Casas, L. M., additional, Conti, E., additional, Bell, S., additional, Prydderch, M. L., additional, Thomas, S., additional, Christian, D. C., additional, Deptuch, G., additional, Fahim, F., additional, Hoff, J., additional, Lipton, R., additional, Liu, T., additional, Zimmerman, T., additional, Miryala, S., additional, Garcia-Sciveres, M., additional, Gnani, D., additional, Krieger, A., additional, Papadopoulou, K., additional, Heim, T., additional, Carney, R., additional, Nachman, B., additional, Renteira, C., additional, Wallangen, V., additional, Hoeferkamp, M., additional, and Seidel, S., additional

Published
2018
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7. First measurements of a prototype of a new generation pixel readout ASIC in 65 nm CMOS for extreme rate HEP detectors at HL-LHC

Author

Panati, S., primary, Paterno, A., additional, Monteil, E., additional, Pacher, L., additional, Demaria, N., additional, Rivetti, A., additional, Da Rocha Rolo, M., additional, Wheadon, R., additional, Rotondo, F., additional, Dellacasa, G., additional, Licciulli, F., additional, Loddo, F., additional, Ciciriello, F., additional, Marzocca, C., additional, Mattiazzo, S., additional, De Canio, F., additional, Gaioni, L., additional, Re, V., additional, Traversi, G., additional, Ratti, L., additional, Marconi, S., additional, Magazzu, G., additional, Stabile, A., additional, and Placidi, P., additional

Published
2016
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9. CHIPIX65: Developments on a new generation pixel readout ASIC in CMOS 65 nm for HEP experiments

Author

Demaria, N., primary, Dellacasa, G., additional, Mazza, G., additional, Rivetti, A., additional, Da Rocha Rolo, M. D., additional, Monteil, E., additional, Pacher, L., additional, Ciciriello, F., additional, Corsi, F., additional, Marzocca, C., additional, De Roberts, G., additional, Loddo, F., additional, Tamma, C., additional, Bagatin, M., additional, Bisello, D., additional, Gerardin, S., additional, Mattiazzo, S., additional, Ding, L., additional, Giubilato, P., additional, Paccagnella, A., additional, De Canio, F., additional, Gaioni, L., additional, Manghisoni, M., additional, Re, V., additional, Traversi, G., additional, Riceputi, E., additional, Ratti, L., additional, Vacchi, C., additional, Beccherle, R., additional, Magazzu, G., additional, Minuti, M., additional, Morsani, F., additional, Palla, F., additional, Liberali, V., additional, Shojaii, S., additional, Stabile, A., additional, Bilei, G. M., additional, Menichelli, M., additional, Conti, E., additional, Marconi, S., additional, Passen, D., additional, and Placidi, P., additional

Published
2015
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11. Graph Rigidity, Cyclic Belief Propagation, and Point Pattern Matching.

Author

McAuley, Julian J., Caetano, Tibérlo S., and Barbosa, Marconi S.

Subjects
GRAPHICAL modeling (Statistics), STATISTICAL matching, COMPUTER algorithms, PATTERN recognition systems, RANDOM noise theory, WHITE noise theory, OPTIMAL designs (Statistics)
Abstract

A recent paper [1] proposed a provably optimal polynomial time method for performing near-isometric point pattern matching by means of exact probabilistic inference in a chordal graphical model. Its fundamental result is that the chordal graph in question is shown to be globally rigid, implying that exact inference provides the same matching solution as exact inference in a complete graphical model. This implies that the algorithm is optimal when there is no noise in the point patterns. In this paper, we present a new graph that is also globally rigid but has an advantage over the graph proposed in [1]: Its maximal clique size is smaller, rendering inference significantly more efficient. However, this graph is not chordal, and thus, standard Junction Tree algorithms cannot be directly applied. Nevertheless, we show that loopy belief propagation in such a graph converges to the optimal solution. This allows us to retain the optimality guarantee in the noiseless case, while substantially reducing both memory requirements and processing time. Our experimental results show that the accuracy of the proposed solution is indistinguishable from that in [1] when there is noise in the point patterns. [ABSTRACT FROM AUTHOR]

Published
2008
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