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Literatura académica sobre el tema "Intensité du signal reçu"
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Artículos de revistas sobre el tema "Intensité du signal reçu"
Bergstrom, Victoria. "Entre signal reçu et crypté: Pierre Alferi's Poetics of Remediation". French Forum 45, n.º 2 (2020): 205–21. http://dx.doi.org/10.1353/frf.2020.0016.
Texto completoMoreau, Marc, Catherine Leclerc y Isabelle Néant. "La saga de l’induction neurale : presque un siècle de recherche". médecine/sciences 36, n.º 11 (noviembre de 2020): 1018–26. http://dx.doi.org/10.1051/medsci/2020172.
Texto completoM’Bailara, K., S. Gard, E. Rouan, M. Chive, L. Zanouy, I. Minois, M. Bouteloux, A. Jutant y A. Desage. "Poids de l’évolution des représentations sur les stratégies d’adaptation des patients et des familles confrontées au trouble bipolaire". European Psychiatry 29, S3 (noviembre de 2014): 620. http://dx.doi.org/10.1016/j.eurpsy.2014.09.105.
Texto completoCatros, Véronique. "Les CAR-T cells, des cellules tueuses spécifiques d’antigènes tumoraux". médecine/sciences 35, n.º 4 (abril de 2019): 316–26. http://dx.doi.org/10.1051/medsci/2019067.
Texto completoDe Sloovere, Pierre, Pierre Colin, Jean-Louis Mauss, Hubert Godin y Stefano Priano. "La sismique fréquentielle, outil pour vérifier la continuite de la transmission des contraintes dans un massif applications aux injections, vides, voutes de tunnel". E3S Web of Conferences 504 (2024): 04003. http://dx.doi.org/10.1051/e3sconf/202450404003.
Texto completoReu, Frederic J., Tomas Radivoyevitch, Jason Valent, Chad Cummings, Katherine Tullio, Debbie Hastings, Beth M. Faiman et al. "Response-Adapted Therapy for Newly Diagnosed Myeloma". Blood 128, n.º 22 (2 de diciembre de 2016): 3606. http://dx.doi.org/10.1182/blood.v128.22.3606.3606.
Texto completoZhu, Shuping, Wei Gao y Xiaolei Li. "SSANet: normal-mode interference spectrum extraction via SSA algorithm-unrolled neural network". Frontiers in Marine Science 10 (1 de febrero de 2024). http://dx.doi.org/10.3389/fmars.2023.1342090.
Texto completoCockx, Bart, Muriel Dejemeppe y Bruno Van der Linden. "Numéro 85 (fr) - février 2011". Regards économiques, 12 de octubre de 2018. http://dx.doi.org/10.14428/regardseco.v1i0.15113.
Texto completoCockx, Bart, Muriel Dejemeppe y Bruno Van der Linden. "Numéro 85 (fr) - février 2011". Regards économiques, 12 de octubre de 2018. http://dx.doi.org/10.14428/regardseco2011.02.01.
Texto completoTesis sobre el tema "Intensité du signal reçu"
Le, Minh Hoang. "Various Positioning Algorithms based on Received Signal Strength and/or Time/Direction (Difference) of Arrival for 2D and 3D Scenarios". Electronic Thesis or Diss., Sorbonne université, 2022. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2022SORUS072.pdf.
Texto completoLocalization has fascinated the researchers for centuries and has motivated a large amount of studies and developments in communications. The aim of positioning problems is to determine the position of the mobile device. Positioning algorithms can be divided into 3 methods: Trilateration, Multilateration and Triangulation. Trilateration utilizes the distances between the mobile device and all the base stations around to estimate the mobile position. These distances can be estimated via the Time of Arrival (ToA) or the Received Signal Strength (RSS). In Multilateration, the position location is based on measured quantities whose values are a function of the Time Difference of Arrival (TDoA) of the two ToAs. As for Triangulation, the directions of the incident signals play the most crucial role in the localization. Thus, it is also referred to as Direction-based Localization. The Direction of Arrival (DoA) of each incident wave is taken into account to solve the positioning problem. Each DoA is expressed by a single angle in 2D scenarios, and a pair of angles in 3D scenarios. There are noticeable differences between Network-Positioning and Self-Positioning. In Network-Positioning, the mobile device is directly localized based on the DoAs of the incident signals; meanwhile, in Self-Positioning, its position is estimated by the Direction Difference of Arrival (DDoA) between each pair of incident signals, because the DoA of each signal arriving to the Mobile Device is ambiguous. In this dissertation, we study all the localization approaches described above. Our spotlight is for Triangulation, which has many sub-scenarios to analyze. The results are obtained by MATLAB simulations
Garnier, Carole. "Segmentation de la prostate pour la thérapie par Ultrasons Haute Intensité guidée par l'image". Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00498035.
Texto completoEsneault, Simon. "Planning pour la thérapie de tumeur du foie par ultrasons haute intensité". Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00497749.
Texto completoRoth, Jean-Marc. "Réalisation d'un analyseur optique multi et monocanal associé à une caméra à balayage de fente : application à la métrologie d'impulsions lumineuses à l'échelle de la picoseconde et de très faible intensité". Université Louis Pasteur (Strasbourg) (1971-2008), 1985. http://www.theses.fr/1985STR10004.
Texto completoLiu, Siyang. "Efficient machine learning techniques for indoor localization in wireless communication systems". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST188.
Texto completoWith rapid development of Internet of Things (IoT), the need of indoor location-based services such as asset management, navigation and tracking has also grown overtime. For indoor localization, navigation satellite systems such as GPS has limited usage since a direct line-of-sight to satellites is unavailable.Various solutions have been proposed for indoor localization such as trilateration, triangulation, dead reckoning, but their performance is limited by indoor channel conditions, such as shadowing and multipath fading. By exploiting the mapping between wireless signal feature measurements and positions, fingerprinting based methods have shown the potential to provide good localization performance with sufficient data. However, indoor localization still faces challenges like scalability, cost and complexity, privacy, etc.The focus of this thesis is to improve efficiency of indoor localization using machine learning techniques. We divide the localization process into two phases: offline radio mapping phase and online localization phase. During the offline phase, we introduce dataset analysis as an intermediate step between dataset creation and localization. We propose two numerical dataset quality indicators which can provide feedback to improve the radio map. Moreover, feature extraction and dataset processing using machine learning tools are integrated to improve efficiency by reducing the data size and computation complexity while improving localization performance. We propose a k-means based radio mapping method which can reduce the number of fingerprints by over % without losing useful information in the radio map or degrading localization performance. By exploring the hierarchical nature of large datasets, we propose a hierarchical feature extraction method which can further reduce localization complexity without compromising localization performance.For the online localization phase, we explore both traditional machine learning and deep learning. We first introduce several traditional machine learning methods and compare the localization performance on public datasets. We aim to improve localization performance of traditional methods.To cope with privacy and complexity issue, we introduce federated learning framework for indoor localization problem. In this framework, the clients share only their local models to the central server instead of the fingerprinting data. We first compare the performance with federated and centralized learning. Then, we further study the impact on different client numbers and local data size. To reduce communication cost during the training process, we evaluate different measures including client selection, gradient accumulation and model compression. An efficient compression method is proposed to compress local models which can reduce the uplink communication cost by 91.5% without compromising localization performance. At last, we consider a limit on uplink capacity and evaluate different compression strategies
Bildea, Ana. "Link Quality in Wireless Sensor Networks". Thesis, Grenoble, 2013. http://www.theses.fr/2013GRENM054/document.
Texto completoThe goal of the thesis is to investigate the issues related to the temporal link quality variation in large scale WSN environments, to design energy efficient link quality estimators able to distinguish among links with different quality on a short and a long term. First, we investigate the characteristics of two physical layer metrics: RSSI (Received Signal Strength Indication) and LQI (Link Quality Indication) on SensLAB, an indoor large scale wireless sensor network testbed. We observe that RSSI and LQI have distinct values that can discriminate the quality of links. Second, to obtain an estimator of PRR, we have fitted a Fermi-Dirac function to the scatter diagram of the average and standard variation of LQI and RSSI. The function enables us to find PRR for a given level of LQI. We evaluate the estimator by computing PRR over a varying size window of transmissions and comparing with the estimator. Furthermore, we show using the Gilbert-Elliot two-state Markov model that the correlation of packet losses and successful receptions depend on the link category. The model allows to accurately distinguish among strongly varying intermediate links based on transition probabilities derived from the average and the standard variation of LQI. Finally, we propose a link quality routing model driven from the F-D fitting functions and the Markov model able to discriminate accurately link categories as well as high variable links
Abdmouleh, Ahmed. "Codes correcteurs d'erreurs NB-LDPC associés aux modulations d'ordre élevé". Thesis, Lorient, 2017. http://www.theses.fr/2017LORIS452/document.
Texto completoThis thesis is devoted to the analysis of the association of non-binary LDPC codes (NB-LDPC) with high-order modulations. This association aims to improve the spectral efficiency of future wireless communication systems. Our approach tries to take maximum advantage of the straight association between NB-LDPC codes over a Galois Field with modulation constellations of the same cardinality. We first investigate the optimization of the signal space diversity technique obtained with the Rayleigh channel (with and without erasure) thanks to the rotation of the constellation. To optimize the rotation angle, the mutual information analysis is performed for both coded modulation (CM) and bit-interleaved coded modulation (BICM) schemes. The study shows the advantages of coded modulations over the state-of-the-art BCIM modulations. Using Monte Carlo simulation, we show that the theoretical gains translate into actual gains in practical systems. In the second part of the thesis, we propose to perform a joint optimization of constellation labeling and parity-check coefficient choice, based on the Euclidian distance instead of the Hamming distance. An optimization method is proposed. Using the optimized matrices, a gain of 0.2 dB in performance is obtained with no additional complexity
Njima, Wafa. "Méthodes de localisation de capteurs dans le contexte de l'Internet des Objets". Electronic Thesis or Diss., Paris, CNAM, 2019. http://www.theses.fr/2019CNAM1264.
Texto completoWith the growing emergence of the Internet of Things and the importance of position information in this context, localization is attracting more and more attention in the researchers' community. The outdoor location is provided by GPS which is not suitable for indoors environments. Several indoor localization techniques exist, but there is not yet a standard.Existing methods are mainly based on trilateration or fingerprinting. Trilateration is a geometric method that exploits thedistances between an object and reference points to locate it. This method only works when we have at least 3 access points detected and is strongly affected by multi paths. In order to overcome these disadvantages, the fingerprinting methodcompares the fingerprint associated to the object to be located to a fingerprints' database constructed on offline. The estimated position is a combination of the selected training positions. This method is of great interest. However, it requiressignificant computing and storage capabilities. The aim of this thesis is to improve the existing localization techniqueswhile maintaining a satisfying localization accuracy with low computational complexity. In order to overcome the disadvantages of these two classes of localization techniques, we propose alternative approaches. For trilateration, it hasbeen combined with an optimization process that aims at completing the inter-node distance matrix from partially knowndata. Advanced optimization algorithms have been used in developing the mathematical equation corresponding to eachone. Using this method, we came up with a localization solution for a distributed IoT architecture. As for fingerprinting, we have exploited it to develop localization systems for a centralized IoT architecture. A comparative study between different metrics of similarity evaluation is conducted. This study was followed by the development of a linear model generating a mathematical relation that links the powers of the signal received by an object to its coordinates. This helps to reduce the online complexity of and adapts our system to real time. This is also ensured by the development of a CNN model which deal with the localization problem as radio images classification problem. The performances of all proposed approaches are evaluated and discussed. These results show the improvement of the performances of basic techniques in terms of localization accuracy and complexity
Informes sobre el tema "Intensité du signal reçu"
African Open Science Platform Part 1: Landscape Study. Academy of Science of South Africa (ASSAf), 2019. http://dx.doi.org/10.17159/assaf.2019/0047.
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