Literatura académica sobre el tema "Linear Sampling Method (LSM)"
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Artículos de revistas sobre el tema "Linear Sampling Method (LSM)"
Narumanchi, Venkatalakshmi V., Fatemeh Pourahmadian, Jordan Lum, Andrew Townsend, Joseph W. Tringe, David M. Stobbe y Todd W. Murray. "Laser ultrasonic imaging of subsurface defects with the linear sampling method". Optics Express 31, n.º 5 (24 de febrero de 2023): 9098. http://dx.doi.org/10.1364/oe.485084.
Texto completoSun, Jiyu y Yuhui Han. "Two-Step Extended Sampling Method for the Inverse Acoustic Source Problem". Mathematical Problems in Engineering 2020 (7 de febrero de 2020): 1–8. http://dx.doi.org/10.1155/2020/6434607.
Texto completoSalarkaleji, Mehdi, Mohammadreza Eskandari, Jimmy Chen y Chung-Tse Wu. "Frequency and Polarization-Diversified Linear Sampling Methods for Microwave Tomography and Remote Sensing Using Electromagnetic Metamaterials". Electronics 6, n.º 4 (18 de octubre de 2017): 85. http://dx.doi.org/10.3390/electronics6040085.
Texto completoHossain, F., E. N. Anagnostou y K. H. Lee. "A non-linear and stochastic response surface method for Bayesian estimation of uncertainty in soil moisture simulation from a land surface model". Nonlinear Processes in Geophysics 11, n.º 4 (24 de septiembre de 2004): 427–40. http://dx.doi.org/10.5194/npg-11-427-2004.
Texto completoDi Donato, Loreto, Rosa Scapaticci, Tommaso Isernia, Ilaria Catapano y Lorenzo Crocco. "An Effective Method for Borehole Imaging of Buried Tunnels". International Journal of Antennas and Propagation 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/246472.
Texto completoKuo, Yu-Hsin y Jean-Fu Kiang. "An Iterative Approach to Improve Images of Multiple Targets and Targets with Layered or Continuous Profile". International Journal of Microwave Science and Technology 2015 (27 de septiembre de 2015): 1–13. http://dx.doi.org/10.1155/2015/376374.
Texto completoGuerriero, Vincenzo. "Maximum Likelihood Instead of Least Squares in Fracture Analysis by Means of a Simple Excel Sheet with VBA Macro". Geosciences 13, n.º 12 (11 de diciembre de 2023): 379. http://dx.doi.org/10.3390/geosciences13120379.
Texto completoZeng, Pengyuan, Xuan Song, Huan Yang, Ning Wei y Liping Du. "Digital Soil Mapping of Soil Organic Matter with Deep Learning Algorithms". ISPRS International Journal of Geo-Information 11, n.º 5 (6 de mayo de 2022): 299. http://dx.doi.org/10.3390/ijgi11050299.
Texto completoMeng, Shuo, Chen Meng, Cheng Wang y Xiang Yin. "A Method Based on Random Demodulator and Waveform Matching Dictionary to Estimate LFM Signal Parameter". Journal of Sensors 2023 (22 de marzo de 2023): 1–11. http://dx.doi.org/10.1155/2023/2499336.
Texto completoJia, Pengxiang, Jianhua Yang, Chengjin Wu y Miguel A. F. Sanjuán. "Amplification of the LFM signal by using piecewise vibrational methods". Journal of Vibration and Control 25, n.º 1 (24 de abril de 2018): 141–50. http://dx.doi.org/10.1177/1077546318772257.
Texto completoTesis sobre el tema "Linear Sampling Method (LSM)"
Hörmann, Wolfgang y Josef Leydold. "Sampling from Linear Multivariate Densities". WU Vienna University of Economics and Business, 2009. http://epub.wu.ac.at/3192/1/Report111.pdf.
Texto completoSeries: Research Report Series / Department of Statistics and Mathematics
Recoquillay, Arnaud. "Méthodes d'échantillonnage appliquées à l'imagerie de défauts dans un guide d'ondes élastiques". Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLY001/document.
Texto completoWidely used structures in an industrial context, such as plates, pipes or rails, can be considered as waveguides. Hence efficient Non Destructive Testing techniques are needed in order to detect defects in these structure during their maintenance. This work is about adapting a sampling method, the Linear Sampling Method, to the context of NDT for elastic waveguides. This context implies that the sollicitations and measurements must be on the surface of the waveguide in a time-dependent regime. A modal and multi-frequency formulation of the LSM, specific to waveguides, has been chosen to solve the problem. This formulation allows an efficient and physical regularization of the inverse problem, which is naturally ill-posed. An optimization of the number of sources and measurements and of their positioning is possible thanks to the methodology used to solve the problem. The scalar case of an acoustic waveguide is considered as a first step, while the vectorial case of an elastic waveguide, more complex by nature, is addressed in a second time.The efficiency of the method is at first tested on artificial data (numerically made), and then on real data obtained from experiments on metallic plates. These experiments show the feasibility of using sampling methods for Non Destructive Testing in an industrial context. In the case when only one sollicitation is available, the LSM can not be applied. A completely different approach is then used, which is called the ``exterior'' approach, coupling a mixed formulation of quasi-reversibility and a level-set method in order to recover the shape of the defect
Oliveira, Hugo Luiz. "Modelos numéricos aplicados à análise viscoelástica linear e à otimização topológica probabilística de estruturas bidimensionais: uma abordagem pelo Método dos Elementos de Contorno". Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/18/18134/tde-27042017-093145/.
Texto completoThe present work deals with the formulation and implementation of numerical models based on the Boundary Element Method (BEM). Inspired by engineering problems, a multidisciplinary combination is proposed as a more realistic approach. There are common engineering materials that have time-dependent response. In this thesis, time-dependent phenomena are approached through the Linear Viscoelastic Mechanics associated with rheological models. In this work, the formulation of Maxwell\'s constitutive model is presented to be used via MEC. The resultant equations are checked on reference problems. The results show that the presented formulation can be used to represent composite structures, even in cases involving a junction between viscoelastic and non-viscoelastic materials. Additionally the formulations presented remain stable in the presence of cracks. It is found that the classical DUAL-BEM formulation can be used to simulate cracks with time-dependent behaviour. This result serves as the basis for further investigations in the field of Fracture Mechanics of viscoelastic materials. In the sequence, it is shown how the BEM can be associated with probabilistic concepts to make predictions of long-term behaviour. These predictions include the inherent uncertainties in engineering processes. The uncertainties involve the material, loading and geometry parameters. Using the concept of probability of failure, the results show that the uncertainties related to the estimations of loads have important impact on the long-term expected performance. This finding serves to carry out studies that collaborate for the improvement of structural design processes. Another aspect of interest of this thesis is the search for optimized forms through Topological Optimization. In this work, an alternative topological optimization algorithm is proposed. The algorithm is based on the coupling between the Level Set Method (LSM) and BEM. The difference between the algorithm proposed here, and the others present in the literature, is a way of obtaining the velocity field. In this thesis, the normal fields of velocities are obtained by means of shape sensitivity. This change makes the algorithm adequate to be treated by the BEM, since the information necessary for the calculation of the sensitivities resides exclusively in the contour. It is found that the algorithm requires a particular velocity extension in order to maintain stability. Limiting to two-dimensional cases, the algorithm is able to obtain the known benchmark cases reported in the literature. The last aspect addressed in this thesis involves the way in which geometric uncertainties can influence the determination of optimized structures. Using the BEM, it is proposed a probabilistic criterion that takes into consideration the geometric sensitivity. The results show that deterministic criteria do not always lead to the most appropriate choices from an engineering point of view. In summary, this work contributes to the expansion and diffusion of MEC applications in structural engineering problems.
Alqadah, Hatim F. "Space-Frequency Regularization for Qualitative Inverse Scattering". University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1321967202.
Texto completoDelbary, Fabrice. "Identification de fissures par ondes acoustiques". Paris 6, 2006. http://www.theses.fr/2006PA066605.
Texto completoAssareh, Hassan. "Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals". Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/53342/1/Hassan_Assareh_Thesis.pdf.
Texto completoAhmed, Mohamed Salem. "Contribution à la statistique spatiale et l'analyse de données fonctionnelles". Thesis, Lille 3, 2017. http://www.theses.fr/2017LIL30047/document.
Texto completoThis thesis is about statistical inference for spatial and/or functional data. Indeed, weare interested in estimation of unknown parameters of some models from random or nonrandom(stratified) samples composed of independent or spatially dependent variables.The specificity of the proposed methods lies in the fact that they take into considerationthe considered sample nature (stratified or spatial sample).We begin by studying data valued in a space of infinite dimension or so-called ”functionaldata”. First, we study a functional binary choice model explored in a case-controlor choice-based sample design context. The specificity of this study is that the proposedmethod takes into account the sampling scheme. We describe a conditional likelihoodfunction under the sampling distribution and a reduction of dimension strategy to definea feasible conditional maximum likelihood estimator of the model. Asymptotic propertiesof the proposed estimates as well as their application to simulated and real data are given.Secondly, we explore a functional linear autoregressive spatial model whose particularityis on the functional nature of the explanatory variable and the structure of the spatialdependence. The estimation procedure consists of reducing the infinite dimension of thefunctional variable and maximizing a quasi-likelihood function. We establish the consistencyand asymptotic normality of the estimator. The usefulness of the methodology isillustrated via simulations and an application to some real data.In the second part of the thesis, we address some estimation and prediction problemsof real random spatial variables. We start by generalizing the k-nearest neighbors method,namely k-NN, to predict a spatial process at non-observed locations using some covariates.The specificity of the proposed k-NN predictor lies in the fact that it is flexible and allowsa number of heterogeneity in the covariate. We establish the almost complete convergencewith rates of the spatial predictor whose performance is ensured by an application oversimulated and environmental data. In addition, we generalize the partially linear probitmodel of independent data to the spatial case. We use a linear process for disturbancesallowing various spatial dependencies and propose a semiparametric estimation approachbased on weighted likelihood and generalized method of moments methods. We establishthe consistency and asymptotic distribution of the proposed estimators and investigate thefinite sample performance of the estimators on simulated data. We end by an applicationof spatial binary choice models to identify UADT (Upper aerodigestive tract) cancer riskfactors in the north region of France which displays the highest rates of such cancerincidence and mortality of the country
Stampfer, Kilian. "The Generalized Operator Based Prony Method". Doctoral thesis, 2019. http://hdl.handle.net/11858/00-1735-0000-002E-E631-3.
Texto completoErhard, Klaus. "Point Source Approximation Methods in Inverse Obstacle Reconstruction Problems". Doctoral thesis, 2005. http://hdl.handle.net/11858/00-1735-0000-0006-B402-4.
Texto completoLibros sobre el tema "Linear Sampling Method (LSM)"
1943-, Colton David L. y Monk Peter 1956-, eds. The linear sampling method in inverse electromagnetic scattering. Philadelphia: Society for Industrial and Applied Mathematics, 2011.
Buscar texto completoRajeev, S. G. Spectral Methods. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805021.003.0013.
Texto completoCapítulos de libros sobre el tema "Linear Sampling Method (LSM)"
Colton, David, Andreas Kirsch y Peter Monk. "The Linear Sampling Method in Inverse Scattering Theory". En Surveys on Solution Methods for Inverse Problems, 107–18. Vienna: Springer Vienna, 2000. http://dx.doi.org/10.1007/978-3-7091-6296-5_6.
Texto completoCollino, Francis, M’Barek Fares y Houssem Haddar. "On the Validation of the Linear Sampling Method in Electromagnetic Inverse Scattering Problems". En Mathematical and Numerical Aspects of Wave Propagation WAVES 2003, 649–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55856-6_105.
Texto completoPetersson, Andreas. "Rapid Covariance-Based Sampling of Linear SPDE Approximations in the Multilevel Monte Carlo Method". En Springer Proceedings in Mathematics & Statistics, 423–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43465-6_21.
Texto completoGoshtasbpour, Shirin y Fernando Perez-Cruz. "Optimization of Annealed Importance Sampling Hyperparameters". En Machine Learning and Knowledge Discovery in Databases, 174–90. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-26419-1_11.
Texto completoFaddila, Syifa Pramudita, Citra Savitri, Dedi Mulyadi y Puji Isyanto. "Flash Sale and Brand Image Models in Improving Purchase Decisions on Fashion Products at the Shopee Marketplace Among Students". En Proceedings of the 19th International Symposium on Management (INSYMA 2022), 841–48. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-008-4_105.
Texto completoPrillya, Laurasia Trya, Prihatin Lumbanraja y Meilita Tryana Sembiring. "Analysis of Job Satisfaction, Job Stress, and Job Insecurity on Employee Turnover Intention at a Manufacturing Company in the Industrial and Chemical Sector in North Sumatra". En Proceedings of the 19th International Symposium on Management (INSYMA 2022), 664–71. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-008-4_83.
Texto completoRyou, Wonryong, Jiayu Chen, Mislav Balunovic, Gagandeep Singh, Andrei Dan y Martin Vechev. "Scalable Polyhedral Verification of Recurrent Neural Networks". En Computer Aided Verification, 225–48. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_10.
Texto completoSitorus, Ombun Rico, Sukaria Sinulingga y Beby Karina Fawzeea Sembiring. "Green Marketing Strategy Effect on Consumer Awareness Through Marketing Mix Approach". En Proceedings of the 19th International Symposium on Management (INSYMA 2022), 976–81. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-008-4_121.
Texto completoTran, Hoang-Dung, Neelanjana Pal, Patrick Musau, Diego Manzanas Lopez, Nathaniel Hamilton, Xiaodong Yang, Stanley Bak y Taylor T. Johnson. "Robustness Verification of Semantic Segmentation Neural Networks Using Relaxed Reachability". En Computer Aided Verification, 263–86. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_12.
Texto completoIrawati, Indrarini Dyah, Gelar Budiman, Kholidiyah Masykuroh, Zein Hanni Pradana y Arfianto Fahmi. "High Payload Qr-Based Data Hiding Using Secured Compressed Watermark in Polar Domain". En Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210285.
Texto completoActas de conferencias sobre el tema "Linear Sampling Method (LSM)"
Catapano, I., Francesco Soldovieri, Lorenzo Crocco, Loreto Di Donato y Raffaele Persico. "Utilities mapping via Linear Sampling Method". En 2012 14th International Conference on Ground Penetrating Radar (GPR). IEEE, 2012. http://dx.doi.org/10.1109/icgpr.2012.6254881.
Texto completoKim, Hyun-Chul, Kyu-Hwan Jung y Jaewook Lee. "Approximate Sampling Method for Locally Linear Embedding". En 2007 International Joint Conference on Neural Networks. IEEE, 2007. http://dx.doi.org/10.1109/ijcnn.2007.4371023.
Texto completoBurfeindt, Matthew J. y Hatim F. Alqadah. "Receive-beamforming-enhanced Linear Sampling Method imaging". En 2021 IEEE Research and Applications of Photonics in Defense Conference (RAPID). IEEE, 2021. http://dx.doi.org/10.1109/rapid51799.2021.9521380.
Texto completoXue, Junliang, Yongjun Wang, Chao Li, Jingwen Liu, Lu Han, Qi Zhang y Xiangjun Xin. "Integration Extraction Method Aided Linear Optical Sampling System". En 2022 20th International Conference on Optical Communications and Networks (ICOCN). IEEE, 2022. http://dx.doi.org/10.1109/icocn55511.2022.9901118.
Texto completoAmbrosanio, M., M. T. Bevacqua, T. Isernia y V. Pascazio. "Experimental Multistatic Imaging VIA the Linear Sampling Method". En IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8897877.
Texto completoCHARALAMBOPOULOS, ANTONIOS, DROSSOS GINTIDES y KIRIAKIE KIRIAKI. "THE LINEAR SAMPLING METHOD FOR N-BODIES IN 2-DIMENSIONAL LINEAR ELASTICITY". En Proceedings of the Sixth International Workshop. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702593_0024.
Texto completoHaghparast, Maysam, Seyed Abdullah Mirtaheri y Mohammad Sadegh Abrishamian. "Conductor and dielectric object discrimination by linear sampling method". En 2016 24th Iranian Conference on Electrical Engineering (ICEE). IEEE, 2016. http://dx.doi.org/10.1109/iraniancee.2016.7585661.
Texto completoMallikarjun, E., Abhishek Roy y Amitabha Bhattacharya. "Effect of multipoles in resolution with Linear Sampling Method". En 2014 Twentieth National Conference on Communications (NCC). IEEE, 2014. http://dx.doi.org/10.1109/ncc.2014.6811352.
Texto completoAlqadah, Hatim F., Jason Parker, Matthew Ferrara y Howard Fan. "Space-frequency sparse regularization for the linear sampling method". En Propagation in Wireless Communications (ICEAA). IEEE, 2011. http://dx.doi.org/10.1109/iceaa.2011.6046376.
Texto completoPrunty, Aaron y Roel Snieder. "Imaging, focusing, and inversion with the linear sampling method". En SEG Technical Program Expanded Abstracts 2019. Society of Exploration Geophysicists, 2019. http://dx.doi.org/10.1190/segam2019-3215188.1.
Texto completoInformes sobre el tema "Linear Sampling Method (LSM)"
Colton, David y Peter Monk. Linear Sampling Method. Fort Belvoir, VA: Defense Technical Information Center, marzo de 1999. http://dx.doi.org/10.21236/ada368321.
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