Relevant bibliographies by topics / Nonlinear reconstruction

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  2. Dissertations / Theses
  3. Books
  4. Book chapters
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Academic literature on the topic 'Nonlinear reconstruction'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Nonlinear reconstruction"

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Yu, Yu, Hong-Ming Zhu, and Ue-Li Pen. "Halo Nonlinear Reconstruction." Astrophysical Journal 847, no. 2 (2017): 110. http://dx.doi.org/10.3847/1538-4357/aa89e7.

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Amat, Sergio, Alberto Magreñan, Juan Ruiz, Juan Carlos Trillo, and Dionisio F. Yañez. "On the Application of the Generalized Means to Construct Multiresolution Schemes Satisfying Certain Inequalities Proving Stability." Mathematics 9, no. 5 (2021): 533. http://dx.doi.org/10.3390/math9050533.

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Multiresolution representations of data are known to be powerful tools in data analysis and processing, and they are particularly interesting for data compression. In order to obtain a proper definition of the edges, a good option is to use nonlinear reconstructions. These nonlinear reconstruction are the heart of the prediction processes which appear in the definition of the nonlinear subdivision and multiresolution schemes. We define and study some nonlinear reconstructions based on the use of nonlinear means, more in concrete the so-called Generalized means. These means have two interesting
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Kaiser, Nick. "Nonlinear cluster lens reconstruction." Astrophysical Journal 439 (January 1995): L1. http://dx.doi.org/10.1086/187730.

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Andia, B. I., K. D. Sauer, and C. A. Bouman. "Nonlinear backprojection for tomographic reconstruction." IEEE Transactions on Nuclear Science 49, no. 1 (2002): 61–68. http://dx.doi.org/10.1109/tns.2002.998682.

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Allingham, David, Matthew West, and Alistair I. Mees. "Wavelet Reconstruction of Nonlinear Dynamics." International Journal of Bifurcation and Chaos 08, no. 11 (1998): 2191–201. http://dx.doi.org/10.1142/s0218127498001789.

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We investigate the reconstruction of embedded time-series from chaotic dynamical systems using wavelets. The standard wavelet transforms are not applicable because of the embedding, and we use a basis pursuit method which on its own does not perform very well. When this is combined with a continuous optimizer, however, we obtain very good models. We discuss the success of this method and apply it to some data from a vibrating string experiment.
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Tieng, Quang M., and Viktor Vegh. "Magnetic resonance imaging in nonlinear fields with nonlinear reconstruction." Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering 39B, no. 3 (2011): 128–40. http://dx.doi.org/10.1002/cmr.b.20200.

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Scherf, N., J. Einenkel, L. C. Horn, et al. "Large Histological Serial Sections for Computational Tissue Volume Reconstruction." Methods of Information in Medicine 46, no. 05 (2007): 614–22. http://dx.doi.org/10.1160/me9065.

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Summary Objectives: A proof of principle study was conducted for microscopic tissue volume reconstructions using a new image processing chain operating on alternately stained large histological serial sections. Methods: Digital histological images were obtained from conventional brightfield transmitted light microscopy. A powerful nonparametric nonlinear optical flow-based registration approach was used. In order to apply a simple but computationally feasible sum-of-squared-differences similarity measure even in case of differing histological stainings, a new consistent tissue segmentation pro
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Yu, Yu, and Hong-Ming Zhu. "Nonlinear Reconstruction of the Velocity Field." Astrophysical Journal 887, no. 2 (2019): 265. http://dx.doi.org/10.3847/1538-4357/ab5580.

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Brach, R. Matthew, Raymond M. Brach, and Richard A. Mink. "Nonlinear Optimization in Vehicular Crash Reconstruction." SAE International Journal of Transportation Safety 3, no. 1 (2015): 17–27. http://dx.doi.org/10.4271/2015-01-1433.

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Dobson, D. C. "Phase reconstruction via nonlinear least-squares." Inverse Problems 8, no. 4 (1992): 541–58. http://dx.doi.org/10.1088/0266-5611/8/4/007.

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Dissertations / Theses on the topic "Nonlinear reconstruction"

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Cecchetto, Benjamin Thomas. "Nonlinear blood pattern reconstruction." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/29394.

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We present a method of reconstructing the area of origin for blood droplets given the position and directions of impact stains. This method works for nonlinear trajectories, such as parabolic motion or motion with drag. A model for fitting ellipses to the stains, obtaining impact velocities, blood drop mass and drag coefficient from blood splatter image densities, impact angle and pattern is also provided. We also show how to use this extra data to aid with our estimation. We validate our method in several experiments involving blood splatters at varying velocities and angles.
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Smario, David J. "Multicorrelation analysis and state space reconstruction /." Online version of thesis, 1994. http://hdl.handle.net/1850/11443.

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Humble, Travis Selby. "Nonlinear wave-packet interferometry and molecular state reconstruction /." view abstract or download file of text, 2005. http://wwwlib.umi.com/cr/uoregon/fullcit?p3190522.

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Thesis (Ph. D.)--University of Oregon, 2005.<br>Typescript. Includes vita and abstract. Includes bibliographical references (leaves 218-220). Also available for download via the World Wide Web; free to University of Oregon users.
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Liu, Peng. "Nonlinear statistical approach for 2.5D human face reconstruction." Thesis, University of Newcastle Upon Tyne, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.607166.

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Dicken, Volker. "Simultaneous activity and attenuation reconstruction in emission tomography." Universität Potsdam, 1998. http://opus.kobv.de/ubp/volltexte/2007/1474/.

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In single photon emission computed tomography (SPECT) one is interested in reconstructing the activity distribution f of some radiopharmaceutical. The data gathered suffer from attenuation due to the tissue density µ. Each imaged slice incorporates noisy sample values of the nonlinear attenuated Radon transform (formular at this place in the original abstract) Traditional theory for SPECT reconstruction treats µ as a known parameter. In practical applications, however, µ is not known, but either crudely estimated, determined in costly additional measurements or plainly neglected. We demonstrat
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Ortín, González Silvia. "Nonlinear dynamics reconstruction by neural networks of time-delay chaotic systems." Doctoral thesis, Universidad de Cantabria, 2010. http://hdl.handle.net/10803/31824.

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This thesis is motivated by the intense research in chaos-based communications in the last years. This thesis focuses on the reconstruction of the nonlinear dynamic of time-delay systems by using an embedding-like approach. This method works with a special embedding space that includes both short time and feedback time delayed values of the system variable. We use a new type of modular neural network based on the structure of time-delay systems. We also carefully investigate the time delay identification from the time series, a crucial parameter to construct the special embedding vector. Fina
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Chau, Thi Tuyet Trang. "Non-parametric methodologies for reconstruction and estimation in nonlinear state-space models." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S010/document.

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Le volume des données disponibles permettant de décrire l’environnement, en particulier l’atmosphère et les océans, s’est accru à un rythme exponentiel. Ces données regroupent des observations et des sorties de modèles numériques. Les observations (satellite, in situ, etc.) sont généralement précises mais sujettes à des erreurs de mesure et disponibles avec un échantillonnage spatio-temporel irrégulier qui rend leur exploitation directe difficile. L’amélioration de la compréhension des processus physiques associée à la plus grande capacité des ordinateurs ont permis des avancées importantes da
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Randrianarivony, Maharavo, and Guido Brunnett. "Parallel implementation of curve reconstruction from noisy samples." Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200600519.

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This paper is concerned with approximating noisy samples by non-uniform rational B-spline curves with special emphasis on free knots. We show how to set up the problem such that nonlinear optimization methods can be applied efficiently. This involves the introduction of penalizing terms in order to avoid undesired knot positions. We report on our implementation of the nonlinear optimization and we show a way to implement the program in parallel. Parallel performance results are described. Our experiments show that our program has a linear speedup and an efficiency value close to uni
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Randrianarivony, Maharavo, and Guido Brunnett. "Parallel implementation of surface reconstruction from noisy samples." Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200600524.

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We consider the problem of reconstructing a surface from noisy samples by approximating the point set with non-uniform rational B-spline surfaces. We focus on the fact that the knot sequences should also be part of the unknown variables that include the control points and the weights in order to find their optimal positions. We show how to set up the free knot problem such that constrained nonlinear optimization can be applied efficiently. We describe in detail a parallel implementation of our approach that give almost linear speedup. Finally, we provide numerical results obtained on the Chemn
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Ettehadi, Seyedrohollah. "Model-based and machine learning techniques for nonlinear image reconstruction in diffuse optical tomography." Thèse, Université de Sherbrooke, 2017. http://hdl.handle.net/11143/11895.

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La tomographie optique diffuse (TOD) est une modalité d’imagerie biomédicale 3D peu dispendieuse et non-invasive qui permet de reconstruire les propriétés optiques d’un tissu biologique. Le processus de reconstruction d’images en TOD est difficile à réaliser puisqu’il nécessite de résoudre un problème non-linéaire et mal posé. Les propriétés optiques sont calculées à partir des mesures de surface du milieu à l’étude. Dans ce projet, deux méthodes de reconstruction non-linéaire pour la TOD ont été développées. La première méthode utilise un modèle itératif, une approche encore en développ
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Books on the topic "Nonlinear reconstruction"

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Rahimi Tabar, M. Reza. Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18472-8.

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Schultz, Gerrit. Magnetic Resonance Imaging with Nonlinear Gradient Fields: Signal Encoding and Image Reconstruction. Springer Fachmedien Wiesbaden, 2013.

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Tsang, K. M. Reconstruction of linear and nonlinear continuous time models from discrete time sampled-data systems. University of Sheffield, Dept. of Control Engineering, 1990.

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Billings, S. A. Reconstruction of MIMO nonlinear differential equation models from the generalised frequency response function matrix. University of Sheffield, Dept. of Automatic Control and Systems Engineering, 1996.

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R, Dougherty Edward, ed. Enhancement and restoration of digital documents: Statistical design of nonlinear algorithms. SPIE Optical Engineering Press, 1997.

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Tsang, K. M. A prediction-error estimation algorithm for the reconstruction of linear and nonlinear continuous time models from frequency response data. University of Sheffield, Dept. of Control Engineering, 1991.

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Polites, Michael E. A nonlinear estimator for reconstructing the angular velocity of a spacecraft without rate gyros. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Program, 1991.

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Magnetic Resonance Imaging With Nonlinear Gradient Fields Signal Encoding And Image Reconstruction. Springer-Verlag Berlin and Heidelberg GmbH &, 2013.

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Tabar, M. Reza Rahimi. Analysis and Data-Based Reconstruction of Complex Nonlinear Dynamical Systems: Using the Methods of Stochastic Processes. Springer, 2019.

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Scholl, Marija Strojnik, Victor Gamiz, and Paul Idell. Unconventional Imaging II. SPIE, 2006.

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Book chapters on the topic "Nonlinear reconstruction"

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Abarbanel, Henry D. I. "Reconstruction of Phase Space." In Institute for Nonlinear Science. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-0763-4_2.

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Wurdeman, Shane R. "State-Space Reconstruction." In Nonlinear Analysis for Human Movement Variability. CRC Press, 2018. http://dx.doi.org/10.1201/9781315370651-3.

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Stark, Jaroslav. "Delay Reconstruction: Dynamics versus Statistics." In Nonlinear Dynamics and Statistics. Birkhäuser Boston, 2001. http://dx.doi.org/10.1007/978-1-4612-0177-9_4.

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Eiber, A., H. G. Freitag, and C. Breuninger. "Virtual Reconstruction of Impaired Human Hearing." In Virtual Nonlinear Multibody Systems. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-010-0203-5_27.

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Schultz, Gerrit. "Image Reconstruction in MRI." In Magnetic Resonance Imaging with Nonlinear Gradient Fields. Springer Fachmedien Wiesbaden, 2013. http://dx.doi.org/10.1007/978-3-658-01134-5_2.

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Schultz, Gerrit. "Iterative Reconstruction in PatLoc Imaging." In Magnetic Resonance Imaging with Nonlinear Gradient Fields. Springer Fachmedien Wiesbaden, 2013. http://dx.doi.org/10.1007/978-3-658-01134-5_7.

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Segalman, Daniel J., and Brian F. Feeny. "Modal Methods for Contact Analysis and Contact Force Reconstruction." In Nonlinear Dynamics, Volume 1. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54404-5_20.

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Schultz, Gerrit. "Direct Reconstruction for Cartesian PatLoc Imaging." In Magnetic Resonance Imaging with Nonlinear Gradient Fields. Springer Fachmedien Wiesbaden, 2013. http://dx.doi.org/10.1007/978-3-658-01134-5_5.

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Schultz, Gerrit. "Direct Reconstruction for Radial PatLoc Imaging." In Magnetic Resonance Imaging with Nonlinear Gradient Fields. Springer Fachmedien Wiesbaden, 2013. http://dx.doi.org/10.1007/978-3-658-01134-5_6.

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Khanagha, Vahid, Hussein Yahia, Khalid Daoudi, Oriol Pont, and Antonio Turiel. "Reconstruction of Speech Signals from Their Unpredictable Points Manifold." In Advances in Nonlinear Speech Processing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25020-0_5.

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Conference papers on the topic "Nonlinear reconstruction"

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Seifert, Birger, R. A. Wheatley, R. Rojas-Aedo, et al. "Steps towards Analytical Pulse Reconstruction from Double Spectrograms using a Tomographic Approach." In Nonlinear Optics. OSA, 2017. http://dx.doi.org/10.1364/nlo.2017.nw4a.10.

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Wang, Kai, James G. Titchener, Bryn A. Bell, et al. "Scalable multi-dimensional synthetic space and full state reconstruction in spectral lattices." In Nonlinear Photonics. OSA, 2018. http://dx.doi.org/10.1364/np.2018.npth3i.2.

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Böhm, F., N. B. Grosse, M. Kolarczik, B. Herzog, N. Owschimikow, and U. Woggon. "Quantum State Reconstruction and Photon Statistics for Coherent States interacting with Quantum Dots." In Nonlinear Optics. OSA, 2017. http://dx.doi.org/10.1364/nlo.2017.nth2a.1.

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Nekrasov, Nikita, Boris I. Afinogenov, Natalia G. Kokareva, Vladimir O. Bessonov, Fedyanin A. Andrey, and Ivan I. Bobrinetskiy. "Femtosecond laser reconstruction of graphene field effect transistor." In Nonlinear Optics and Applications XII, edited by Anatoly V. Zayats, Mario Bertolotti, and Alexei M. Zheltikov. SPIE, 2021. http://dx.doi.org/10.1117/12.2589254.

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Zhang, Yuanlong, Tiankuang Zhou, Xuemei Hu, Hao Xie, Qionghai Dai, and Lingjie Kong. "Enhance imaging depth in wide-field two-photon microscopy by extended detection and computational reconstruction." In Nonlinear Optics. OSA, 2019. http://dx.doi.org/10.1364/nlo.2019.ntu1b.1.

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Noble, Joshua, Chen Zhou, William T. Murray, and Zhiwen Liu. "Convolutional neural network reconstruction of ultrashort optical pulses." In Ultrafast Nonlinear Imaging and Spectroscopy VIII, edited by Zhiwen Liu, Demetri Psaltis, and Kebin Shi. SPIE, 2020. http://dx.doi.org/10.1117/12.2571172.

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Lu, Peng, Erik-Jan Van Kampen, and Q. Ping Chu. "Efficient Nonlinear Actuator Fault Reconstruction System." In AIAA Guidance, Navigation, and Control Conference. American Institute of Aeronautics and Astronautics, 2017. http://dx.doi.org/10.2514/6.2017-1263.

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Barsi, Christopher, Wenjie Wan, and Jason W. Fleischer. "Digital Reconstruction of Nonlinear Beam Propagation." In Frontiers in Optics. OSA, 2008. http://dx.doi.org/10.1364/fio.2008.ftum4.

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Barsi, Christopher, Wenjie Wan, and Jason W. Fleischer. "Digital reconstruction of nonlinear beam propagation." In 2008 Conference on Lasers and Electro-Optics (CLEO). IEEE, 2008. http://dx.doi.org/10.1109/cleo.2008.4551319.

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Tharmalingam, Mathiruban, and Kaamran Raahemifar. "A nonlinear dictionary for image reconstruction." In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638052.

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