Littérature scientifique sur le sujet « Spectral networks »
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Articles de revues sur le sujet "Spectral networks"
Wu, Tingzeng, et Huazhong Lü. « Per-Spectral Characterizations of Bicyclic Networks ». Journal of Applied Mathematics 2017 (2017) : 1–5. http://dx.doi.org/10.1155/2017/7541312.
Texte intégralGaiotto, Davide, Gregory W. Moore et Andrew Neitzke. « Spectral Networks ». Annales Henri Poincaré 14, no 7 (8 mars 2013) : 1643–731. http://dx.doi.org/10.1007/s00023-013-0239-7.
Texte intégralAnastasiadis, Johannes, et Michael Heizmann. « GAN-regularized augmentation strategy for spectral datasets ». tm - Technisches Messen 89, no 4 (5 février 2022) : 278–88. http://dx.doi.org/10.1515/teme-2021-0109.
Texte intégralPenttilä, A., H. Hietala et K. Muinonen. « Asteroid spectral taxonomy using neural networks ». Astronomy & ; Astrophysics 649 (mai 2021) : A46. http://dx.doi.org/10.1051/0004-6361/202038545.
Texte intégralAvdic, Senada, Roumiana Chakarova et Imre Pazsit. « Analysis of the experimental positron lifetime spectra by neural networks ». Nuclear Technology and Radiation Protection 18, no 1 (2003) : 16–21. http://dx.doi.org/10.2298/ntrp0301016a.
Texte intégralTanabe, Kazutoshi, Takatoshi Matsumoto, Tadao Tamura, Jiro Hiraishi, Shinnosuke Saeki, Miwako Arima, Chisato Ono et al. « Identification of Chemical Structures from Infrared Spectra by Using Neural Networks ». Applied Spectroscopy 55, no 10 (octobre 2001) : 1394–403. http://dx.doi.org/10.1366/0003702011953531.
Texte intégralCabrol-Bass, D., C. Cachet, C. Cleva, A. Eghbaldar et T. P. Forrest. « Application pratique des réseaux neuro mimétiques aux données spectroscopiques (infrarouge et masse) en vue de l'élucidation structurale ». Canadian Journal of Chemistry 73, no 9 (1 septembre 1995) : 1412–26. http://dx.doi.org/10.1139/v95-176.
Texte intégralPancoska, Petr, Vit Janota et Timothy A. Keiderling. « Interconvertibility of Electronic and Vibrational Circular Dichroism Spectra of Proteins : A Test of Principle Using Neural Network Mapping ». Applied Spectroscopy 50, no 5 (mai 1996) : 658–68. http://dx.doi.org/10.1366/0003702963905916.
Texte intégralHumphries, Mark D., Javier A. Caballero, Mat Evans, Silvia Maggi et Abhinav Singh. « Spectral estimation for detecting low-dimensional structure in networks using arbitrary null models ». PLOS ONE 16, no 7 (2 juillet 2021) : e0254057. http://dx.doi.org/10.1371/journal.pone.0254057.
Texte intégralBunimovich, Leonid, D. J. Passey, Dallas Smith et Benjamin Webb. « Spectral and Dynamic Consequences of Network Specialization ». International Journal of Bifurcation and Chaos 30, no 06 (mai 2020) : 2050091. http://dx.doi.org/10.1142/s0218127420500911.
Texte intégralThèses sur le sujet "Spectral networks"
Lu, Lu. « Spectral-efficient design in modern wireless communications networks ». Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53902.
Texte intégralBandeira, Nuno Filipe Cabrita. « Spectral networks algorithms for de novo interpretation of tandem mass spectra ». Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3274510.
Texte intégralTitle from first page of PDF file (viewed October 2, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 141-152).
Smith, Dallas C. « Network Specializations, Symmetries, and Spectral Properties ». BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/6998.
Texte intégralShorten, David. « Spectral analysis of neutral evolution ». Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27420.
Texte intégralMiao, Guowang. « Cross-layer optimization for spectral and energy efficiency ». Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31807.
Texte intégralCommittee Chair: Li, Geoffrey Ye; Committee Member: Ma, Xiaoli; Committee Member: Stuber, Gordon; Committee Member: Wardi, Yorai; Committee Member: Yu, Xingxing. Part of the SMARTech Electronic Thesis and Dissertation Collection.
Yamamoto, Koji. « Capacity and Spectral Efficiency of Multihop Radio Networks ». 京都大学 (Kyoto University), 2005. http://hdl.handle.net/2433/68891.
Texte intégralAdouane, Amine Mohamed. « Dynamic management of spectral resources in LTE networks ». Thesis, Versailles-St Quentin en Yvelines, 2015. http://www.theses.fr/2015VERS007V/document.
Texte intégralThe exponential growth in the number of communications devices has set out new ambitious targets to meet the ever-increasing demand for user capacity in emerging wireless systems. However, the inherent impairments of communication channels in cellular systems pose constant challenges to meet the envisioned targets. High spectral reuse efficiency was adopted as a solution to higher data rates. Despite its benefits, high spectral reuse leads to increased interference over the network, which degrades performances of mobile users with bad channel quality. To face this added interfence, OFDM (Orthogonal Frequency Division Multiplexing) is used for the new 4th generation network. Thanks to its orthogonality OFDM eliminates the intra-cellular interference, but when the same resources are used in two adjacents cells, the inter-cell interference becomes severe. To get rid of the latter, several methods for Inter-Cell Interference Coordination (ICIC) have been proposed. ICIC allows coordinated radio resources management between multiple cells. The eNodeBs can share resource usage information and interference levels over the X2 interface through LTE-normalized messages. Non-cooperative game theory was largely applied were eNodeBs selfishly selects resource blocks (RBs) in order to minimize interference. In this thesis, we stress on ICIC for the downlink of a cellular OFDMA system in the context of the SOAPS (Spectrum Opportunistic Access in Public Safety) project. This project focuses on the improvement of frequency resource scheduling for Broadband Services provision by PMR (Private Mobile Radio) systems using LTE technologies. We addressed this problem with four different solutions based on Non-cooperative game theory, three algorithms are devoted to RB selection in order to manage the interference, while the last one is a power control scheme with power economy and enhanced system performances
Ahmed, Junaid. « Spectral efficiency of CDMA based ad-hoc networks ». Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/spectral-efficiency-of-cdma-based-adhoc-networks(f6d958ac-6778-416e-80a5-2318956dbaf2).html.
Texte intégralLahsen-Cherif, Iyad. « Spectral and Energy Efficiency in 5G Wireless Networks ». Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS506/document.
Texte intégralToday's networks continue to evolve and grow resulting more dense, complex and heterogeneous networks.This leads to new challenges such as finding new models to characterize the nodes distribution in the wireless network and approaches to mitigate interference. On the other hand, the energy consumption of WMNs is a challenging issue mainly in rural areas lacking of default electrical grids. Finding alternative technologies and approaches to reduce the consumed energy of these networks is a interesting task. This thesis focuses on proposing and evaluating interference management models for next generation wireless networks (5G and Very Dense High WLANs), and providing tools and technologies to reduce energy consumption of Wireless Mesh Networks (WMNs). Two different problems are thus studied; naturally the thesis is divided into two parts along the following chapters.The contribution of the first part of the thesis is threefold. Firstly, we develop our interference management coordination (CoMP-JT) model. The main idea of CoMP-JT is to turn signals generating harmful interference into useful signals. We develop a new model where BSs inside the coordinated set send a copy of data to border's users experiencing high interference. We consider the r-l Square point process to model the BSs distribution in the network. We derive network performance in terms of coverage probability and throughput. Additionally, we study the impact of the size of coordination set on the network performance. Secondly, we extend these results and provide a new model adopted for Dense Very high throughput WLANs. We take into consideration constraints of WLANs in our model such as carrier sensing range. Thirdly, we tackle resource allocation strategies to limit the interference in LTE networks. We study three cyclic allocation strategies: (i) the independent allocation, (ii) the static allocation and (iii) the load-dependent strategy. We derive tractable analytical expression of the first and second mean of interference. We validate the model using extensive simulations. Reducing the energy consumption and improving the energy efficiency of WMNs is our concern in the second part of the thesis. Indeed, we aim at studying the impact of directional antennas technology on the performance of WMNs, using both analysis and simulations. Fisrt, We derive the Number of Links (NLs) for the chain and grid topologies for different antennas beams. These results are based on the routing tables of nodes in the network. We consider different scenarios such as 1Source-NDestinations to model the downlink communications, NSources-1Destination to model the uplink communications and the 1Source-1Destination as a baseline scenario. Using ns-3 simulator, we simulate network performance in terms of Mean Loss Ratio, throughput, energy consumption and energy efficiency. Then, we study the impact of number of beams, network topology and size, the placement of the gateway on the network performance. Next, we go beyond simulations and propose an optimization framework minimizing the consumed energy while maximizing the network throughput for DAs WMNs. We consider a weighted objective function combining the energy consumption and the throughput. We use power control to adapt transmission power depending on the location of the next hop. This model is a first step to approve the obtained simulation results. We use ILOG Cplex solver to find the optimal solution. Results show that DAs improves the network throughput while reduce the energy consumption and that power control allows saving more energy. In this direction, the LCI4D Project aims at providing low cost infrastructure to connect isolated rural and sub-urban areas to the Internet. In order to reduce the installation and maintenance costs, LCI4D proposes the usage of self-configured Wireless Mesh Networks (WMNs) to connect multimode outdoor femtocells to the remote Marco cell (gateway)
Kunegis, Jérôme [Verfasser]. « On the Spectral Evolution of Large Networks / Jérôme Kunegis ». Koblenz : Universitätsbibliothek Koblenz, 2011. http://d-nb.info/1017370893/34.
Texte intégralLivres sur le sujet "Spectral networks"
Zhou, Xiang, et Chongjin Xie, dir. Enabling Technologies for High Spectral-Efficiency Coherent Optical Communication Networks. Hoboken, NJ, USA : John Wiley & Sons, Inc, 2016. http://dx.doi.org/10.1002/9781119078289.
Texte intégralKrogmeier, J. V. Wireless local area network for ITS communications using the 220 MHz ITS spectral allocation. West Lafayette, IN : Joint Highway Research Project, Purdue University, 2000.
Trouver le texte intégralOllikainen, Olavi. Applications of persistent spectral hole burning in ultrafast optical neural networks, time-resolved spectroscopy and holographic interferometry. Tartu : Tartu University Press, 1996.
Trouver le texte intégralSpectrum and network measurements. Atlanta, Ga : Noble Pub. Corp., 2001.
Trouver le texte intégralWitte, Robert A. Spectrum and network measurements. Englewood Cliffs, N.J : Prentice Hall, 1993.
Trouver le texte intégralAnn, Frazier, et Geological Survey (U.S.). National Mapping Division, dir. Land cover classification from SPOT multispectral and panchromatic images using neural network classification of fuzzy clustered spectral and textural features. [Reston, Va.] : U.S. Dept. of the Interior, U.S. Geological Survey, National Mapping Division, 1995.
Trouver le texte intégralLemeshewsky, George. Land cover classification from SPOT multispectral and panchromatic images using neural network classification of fuzzy clustered spectral and textural features. [Reston, VA] : U.S. Geological Survey, 1995.
Trouver le texte intégralGraph spectra for complex networks. Cambridge : Cambridge University Press, 2011.
Trouver le texte intégralSpectrum and network measurements. Englewood Cliffs, N.J : Prentice Hall, 1991.
Trouver le texte intégralUnited States. National Aeronautics and Space Administration., dir. Marine optical characterizations : Quarterly report. [Washington, DC : National Aeronautics and Space Administration, 1995.
Trouver le texte intégralChapitres de livres sur le sujet "Spectral networks"
Dorogovtsev, Sergei N., Alexander V. Goltsev, José F. F. Mendes et Alexander N. Samukhin. « Spectral Analysis of Random Networks ». Dans Complex Networks, 35–50. Berlin, Heidelberg : Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-44485-5_2.
Texte intégralBlekas, Konstantinos, K. Christodoulidou et I. E. Lagaris. « Newtonian Spectral Clustering ». Dans Artificial Neural Networks – ICANN 2009, 145–54. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04277-5_15.
Texte intégralDemirel-Frank, Semra. « Spectral Inequalities for Quantum Graphs ». Dans Mathematical Technology of Networks, 65–80. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16619-3_6.
Texte intégralDai, Qionghai, et Yue Gao. « Neural Networks on Hypergraph ». Dans Artificial Intelligence : Foundations, Theory, and Algorithms, 121–43. Singapore : Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0185-2_7.
Texte intégralKurucz, Miklós, András A. Benczúr, Károly Csalogány et László Lukács. « Spectral Clustering in Social Networks ». Dans Advances in Web Mining and Web Usage Analysis, 1–20. Berlin, Heidelberg : Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00528-2_1.
Texte intégralKunegis, Jérôme. « Spectral Evolution of Social Networks ». Dans Encyclopedia of Social Network Analysis and Mining, 1–9. New York, NY : Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_125-1.
Texte intégralPalmer, William R., et Tian Zheng. « Spectral Clustering for Directed Networks ». Dans Complex Networks & ; Their Applications IX, 87–99. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65347-7_8.
Texte intégralKunegis, Jérôme. « Spectral Evolution of Social Networks ». Dans Encyclopedia of Social Network Analysis and Mining, 2040–47. New York, NY : Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_125.
Texte intégralFarhi, Haider, et Abderraouf Messai. « Spectral Capacity in Cognitive Networks ». Dans Smart Innovation, Systems and Technologies, 423–29. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21009-0_41.
Texte intégralKunegis, Jérôme. « Spectral Evolution of Social Networks ». Dans Encyclopedia of Social Network Analysis and Mining, 2964–71. New York, NY : Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_125.
Texte intégralActes de conférences sur le sujet "Spectral networks"
Li, Yuan, Zunyue Zhang, Yi Wang, Yue Yu, Xuetong Zhou, Hon Ki Tsang et Xiankai Sun. « Inverse-designed linear coherent photonic networks for high-resolution spectral reconstruction ». Dans CLEO : Science and Innovations. Washington, D.C. : Optica Publishing Group, 2023. http://dx.doi.org/10.1364/cleo_si.2023.sth4g.1.
Texte intégralJin, Shengmin, et Reza Zafarani. « The Spectral Zoo of Networks : Embedding and Visualizing Networks with Spectral Moments ». Dans KDD '20 : The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA : ACM, 2020. http://dx.doi.org/10.1145/3394486.3403195.
Texte intégralFeuer, Mark D., Mario V. Bnyamin et Xin Jiang. « Mitigation of Spectral Slicing Penalty Using Binary Polarization-Shift Keying ». Dans Photonic Networks and Devices. Washington, D.C. : OSA, 2019. http://dx.doi.org/10.1364/networks.2019.neth3d.5.
Texte intégralGopalan, Abishek, Onur Turkcu, Biao Lu et Parthiban Kandappan. « Spectral Efficiencies of WDM Network Architectures with Sliceable Bandwidth Variable Transponders ». Dans Photonic Networks and Devices. Washington, D.C. : OSA, 2017. http://dx.doi.org/10.1364/networks.2017.netu1b.3.
Texte intégralParvin, B., Z. N. Ghosh, L. Heiser, M. Knapp, C. Talcott, K. Laderoute, J. Gray et P. Spellman. « Spectral Decomposition of Signaling Networks ». Dans 2007 4th Symposium on Computational Intelligence in Bioinformatics and Computational Biology. IEEE, 2007. http://dx.doi.org/10.1109/cibcb.2007.4221207.
Texte intégralZheng, Q., et D. B. Skillicorn. « Spectral Embedding of Signed Networks ». Dans Proceedings of the 2015 SIAM International Conference on Data Mining. Philadelphia, PA : Society for Industrial and Applied Mathematics, 2015. http://dx.doi.org/10.1137/1.9781611974010.7.
Texte intégralZheng, Q., et D. B. Skillicorn. « Spectral Embedding of Directed Networks ». Dans ASONAM '15 : Advances in Social Networks Analysis and Mining 2015. New York, NY, USA : ACM, 2015. http://dx.doi.org/10.1145/2808797.2809310.
Texte intégralMoitra, Ankur, et Alexander S. Wein. « Spectral methods from tensor networks ». Dans STOC '19 : 51st Annual ACM SIGACT Symposium on the Theory of Computing. New York, NY, USA : ACM, 2019. http://dx.doi.org/10.1145/3313276.3316357.
Texte intégralPedro, João. « Challenges of Designing Transparent Flexible-Grid Optical Networks for Maximum Spectral Efficiency ». Dans Photonic Networks and Devices. Washington, D.C. : OSA, 2016. http://dx.doi.org/10.1364/networks.2016.new3c.1.
Texte intégralGupta, Anjali, et Brijendra Kumar Joshi. « Spectral Efficiency Evaluation of Network Coded Cognitive Radio Networks ». Dans 2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT). IEEE, 2022. http://dx.doi.org/10.1109/csnt54456.2022.9787641.
Texte intégralRapports d'organisations sur le sujet "Spectral networks"
Sweeney, Matthew, et Emily Shinkle. Understanding Discrete Fracture Networks Through Spectral Graph Theory. Office of Scientific and Technical Information (OSTI), août 2021. http://dx.doi.org/10.2172/1812641.
Texte intégralSweeney, Matthew, et Emily Shinkle. Understanding Discrete Fracture Networks Through Spectral Graph Theory. Office of Scientific and Technical Information (OSTI), août 2021. http://dx.doi.org/10.2172/1812622.
Texte intégralSoloviev, Vladimir, Victoria Solovieva, Anna Tuliakova, Alexey Hostryk et Lukáš Pichl. Complex networks theory and precursors of financial crashes. [б. в.], octobre 2020. http://dx.doi.org/10.31812/123456789/4119.
Texte intégralLiu, Ernest, et Aleh Tsyvinski. Dynamical Structure and Spectral Properties of Input-Output Networks. Cambridge, MA : National Bureau of Economic Research, décembre 2020. http://dx.doi.org/10.3386/w28178.
Texte intégralMayfield, Howard T., Delyle Eastwood et Larry W. Burggraf. Infrared Spectral Classification with Artificial Neural Networks and Classical Pattern Recognition. Fort Belvoir, VA : Defense Technical Information Center, janvier 2000. http://dx.doi.org/10.21236/ada377976.
Texte intégralArmstrong, Derek Elswick, et Joseph Gabriel Gorka. Using Deep Neural Networks to Extract Fireball Parameters from Infrared Spectral Data. Office of Scientific and Technical Information (OSTI), mai 2020. http://dx.doi.org/10.2172/1623398.
Texte intégralSilvester, J. A., et A. Polydoros. Adaptive Spread Spectrum Networks. Fort Belvoir, VA : Defense Technical Information Center, septembre 1987. http://dx.doi.org/10.21236/ada187154.
Texte intégralPursley, Michael B., et Dilip V. Sarwate. Spread Spectrum Radio Networks. Fort Belvoir, VA : Defense Technical Information Center, octobre 1987. http://dx.doi.org/10.21236/ada188914.
Texte intégralSastry, Ambatipudi R. Spread Spectrum Random Access Networks. Fort Belvoir, VA : Defense Technical Information Center, octobre 1993. http://dx.doi.org/10.21236/ada272280.
Texte intégralMcEliece, Robert J. Spectrum Allocation Strategies for Communication Networks. Fort Belvoir, VA : Defense Technical Information Center, octobre 1994. http://dx.doi.org/10.21236/ada294936.
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