Academic literature on the topic 'Inverse problems'
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Journal articles on the topic "Inverse problems"
Coleman, Rodney. "Inverse problems." Journal of Microscopy 153, no. 3 (March 1989): 233–48. http://dx.doi.org/10.1111/j.1365-2818.1989.tb01475.x.
Full textTanaka, Masa, and A. Kassab. "Inverse problems." Engineering Analysis with Boundary Elements 28, no. 3 (March 2004): 181. http://dx.doi.org/10.1016/s0955-7997(03)00048-1.
Full textBunge, Mario. "Inverse Problems." Foundations of Science 24, no. 3 (January 10, 2019): 483–525. http://dx.doi.org/10.1007/s10699-018-09577-1.
Full textRomanov, V. G. "SOME GEOMETRIC ASPECTS IN INVERSE PROBLEMS." Eurasian Journal of Mathematical and Computer Applications 3, no. 1 (2015): 68–84. http://dx.doi.org/10.32523/2306-3172-2015-3-4-68-84.
Full textKabanikhin, S. I., O. I. Krivorotko, D. V. Ermolenko, V. N. Kashtanova, and V. A. Latyshenko. "INVERSE PROBLEMS OF IMMUNOLOGY AND EPIDEMIOLOGY." Eurasian Journal of Mathematical and Computer Applications 5, no. 2 (2017): 14–35. http://dx.doi.org/10.32523/2306-3172-2017-5-2-14-35.
Full textRomanov, V. G. "INVERSE PROBLEMS FOR EQUATIONS WITH A MEMORY." Eurasian Journal of Mathematical and Computer Applications 2, no. 1 (2014): 51–80. http://dx.doi.org/10.32523/2306-3172-2014-2-4-51-80.
Full textIwamoto, Seiichi, and Takayuki Ueno. "INVERSE PARTITION PROBLEMS." Bulletin of informatics and cybernetics 31, no. 1 (March 1999): 67–90. http://dx.doi.org/10.5109/13481.
Full textChu, Moody T. "Inverse Eigenvalue Problems." SIAM Review 40, no. 1 (January 1998): 1–39. http://dx.doi.org/10.1137/s0036144596303984.
Full textGreensite, Fred. "Partial inverse problems." Inverse Problems 22, no. 2 (March 6, 2006): 461–79. http://dx.doi.org/10.1088/0266-5611/22/2/005.
Full textIsakov, Victor. "Inverse obstacle problems." Inverse Problems 25, no. 12 (November 23, 2009): 123002. http://dx.doi.org/10.1088/0266-5611/25/12/123002.
Full textDissertations / Theses on the topic "Inverse problems"
Chen, Xudong 1977. "Inverse problems in electromagnetics." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33933.
Full textVita.
Includes bibliographical references (p. 155-164).
Two inverse problems in electromagnetics are investigated in this thesis. The first is the retrieval of the effective constitutive parameters of metamaterials from the measurement of the reflection and the transmission coefficients. A robust method is proposed for the retrieval of metamaterials as isotropic media, and four improvements over the existing methods make the retrieval results more stable. Next, a new scheme is presented for the retrieval of a specific bianisotropic metamaterial that consists of split-ring resonators, which signifies that the cross polarization terms of the metamaterial are quantitatively investigated for the first time. Finally, an optimization approach is designed to achieve the retrieval of general bianisotropic media with 72 unknown parameters. The hybrid algorithm combining the differential evolution (DE) algorithm and the simplex method steadily converges to the exact solution. The second inverse problem deals with the detection and the classification of buried metallic objects using electromagnetic induction (EMI). Both the exciting and the induced magnetic fields are expanded as a linear combination of basic modes in the spheroidal coordinate system. Due to the orthogonality and the completeness of the spheroidal basic modes, the scattering coefficients are uniquely determined and are characteristics of the object.
(cont.) The scattering coefficients are retrieved from the knowledge of the induced fields, where both synthetic and measurement data are used. The ill-conditioning issue is dealt with by mode truncation and Tikhonov regularization technique. Stored in a library, the scattering coefficients can produce fast forward models for use in pattern matching. In addition, they can be used to train support vector machine (SVM) to sort objects into generic classes.
by Xudong Chen.
Ph.D.
Deolmi, Giulia. "Computational Parabolic Inverse Problems." Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3423351.
Full textIn questa tesi viene presentato un approccio numerico volto alla risoluzione di problemi inversi parabolici, basato sull'utilizzo di una parametrizzazione adattativa. L'algoritmo risolutivo viene descritto per due specici problemi: mentre il primo consiste nella stima della corrosione di una faccia incognita del dominio, il secondo ha come scopo la quanticazione di inquinante immesso in un fiume.
Debarnot, Valentin. "Microscopie computationnelle." Thesis, Toulouse 3, 2020. http://www.theses.fr/2020TOU30156.
Full textThe contributions of this thesis are numerical and theoretical tools for the resolution of blind inverse problems in imaging. We first focus in the case where the observation operator is unknown (e.g. microscopy, astronomy, photography). A very popular approach consists in estimating this operator from an image containing point sources (microbeads or fluorescent proteins in microscopy, stars in astronomy). Such an observation provides a measure of the impulse response of the degradation operator at several points in the field of view. Processing this observation requires robust tools that can rapidly use the data. We propose a toolbox that estimates a degradation operator from an image containing point sources. The estimated operator has the property that at any location in the field of view, its impulse response is expressed as a linear combination of elementary estimated functions. This makes it possible to estimate spatially invariant (convolution) and variant (product-convolution expansion) operators. An important specificity of this toolbox is its high level of automation: only a small number of easily accessible parameters allows to cover a large majority of practical cases. The size of the point source (e.g. bead), the background and the noise are also taken in consideration in the estimation. This tool, coined PSF-estimator, comes in the form of a module for the Fiji software, and is based on a parallelized implementation in C++. The operators generated by an optical system are usually changing for each experiment, which ideally requires a calibration of the system before each acquisition. To overcome this, we propose to represent an optical system not by a single operator (e.g. convolution blur with a fixed kernel for different experiments), but by subspace of operators. This set allows to represent all the possible states of a microscope. We introduce a method for estimating such a subspace from a collection of low rank operators (such as those estimated by the toolbox PSF-Estimator). We show that under reasonable assumptions, this subspace is low-dimensional and consists of low rank elements. In a second step, we apply this process in microscopy on large fields of view and with spatially varying operators. This implementation is possible thanks to the use of additional methods to process real images (e.g. background, noise, discretization of the observation).The construction of an operator subspace is only one step in the resolution of blind inverse problems. It is then necessary to identify the degradation operator in this set from a single observed image. In this thesis, we provide a mathematical framework to this operator identification problem in the case where the original image is constituted of point sources. Theoretical conditions arise from this work, allowing a better understanding of the conditions under which this problem can be solved. We illustrate how this formal study allows the resolution of a blind deblurring problem on a microscopy example.[...]
Kitic, Srdan. "Cosparse regularization of physics-driven inverse problems." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S152/document.
Full textInverse problems related to physical processes are of great importance in practically every field related to signal processing, such as tomography, acoustics, wireless communications, medical and radar imaging, to name only a few. At the same time, many of these problems are quite challenging due to their ill-posed nature. On the other hand, signals originating from physical phenomena are often governed by laws expressible through linear Partial Differential Equations (PDE), or equivalently, integral equations and the associated Green’s functions. In addition, these phenomena are usually induced by sparse singularities, appearing as sources or sinks of a vector field. In this thesis we primarily investigate the coupling of such physical laws with a prior assumption on the sparse origin of a physical process. This gives rise to a “dual” regularization concept, formulated either as sparse analysis (cosparse), yielded by a PDE representation, or equivalent sparse synthesis regularization, if the Green’s functions are used instead. We devote a significant part of the thesis to the comparison of these two approaches. We argue that, despite nominal equivalence, their computational properties are very different. Indeed, due to the inherited sparsity of the discretized PDE (embodied in the analysis operator), the analysis approach scales much more favorably than the equivalent problem regularized by the synthesis approach. Our findings are demonstrated on two applications: acoustic source localization and epileptic source localization in electroencephalography. In both cases, we verify that cosparse approach exhibits superior scalability, even allowing for full (time domain) wavefield interpolation in three spatial dimensions. Moreover, in the acoustic setting, the analysis-based optimization benefits from the increased amount of observation data, resulting in a speedup in processing time that is orders of magnitude faster than the synthesis approach. Numerical simulations show that the developed methods in both applications are competitive to state-of-the-art localization algorithms in their corresponding areas. Finally, we present two sparse analysis methods for blind estimation of the speed of sound and acoustic impedance, simultaneously with wavefield interpolation. This is an important step toward practical implementation, where most physical parameters are unknown beforehand. The versatility of the approach is demonstrated on the “hearing behind walls” scenario, in which the traditional localization methods necessarily fail. Additionally, by means of a novel algorithmic framework, we challenge the audio declipping problemregularized by sparsity or cosparsity. Our method is highly competitive against stateof-the-art, and, in the cosparse setting, allows for an efficient (even real-time) implementation
Baysal, Arzu. "Inverse Problems For Parabolic Equations." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605623/index.pdf.
Full textConnolly, T. John. "Nonlinear methods for inverse problems." Thesis, University of Canterbury. Mathematics, 1989. http://hdl.handle.net/10092/8563.
Full textStewart, K. A. "Inverse problems in signal processing." Thesis, University of Strathclyde, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.382448.
Full textAljohani, Hassan Musallam S. "Wavelet methods and inverse problems." Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/18830/.
Full textMarroquin, J. L. (Jose Luis). "Probabilistic solution of inverse problems." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/15286.
Full textMICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING.
Bibliography: p. 195-200.
by Jose Luis Marroquin.
Ph.D.
Agapiou, Sergios. "Aspects of Bayesian inverse problems." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/60138/.
Full textBooks on the topic "Inverse problems"
Talenti, Giorgio, ed. Inverse Problems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/bfb0072658.
Full textRichter, Mathias. Inverse Problems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9.
Full textRichter, Mathias. Inverse Problems. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9.
Full textCannon, John Rozier, and Ulrich Hornung, eds. Inverse Problems. Basel: Birkhäuser Basel, 1986. http://dx.doi.org/10.1007/978-3-0348-7014-6.
Full textKubo, Shiro, and Mini-Symposium on Inverse Problems (1992 : Hong Kong), eds. Inverse problems. Atlanta, Ga: Atlanta Technology Publications, 1992.
Find full textRamm, A. G. Inverse problems. New York, NY: Springer, 2005.
Find full textInstitute of Physics (Great Britain). Inverse problems. Bristol, England: Institute of Physics, 1985.
Find full textChiachío-Ruano, Juan, Manuel Chiachío-Ruano, and Shankar Sankararaman. Bayesian Inverse Problems. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/b22018.
Full textGol’dman, N. L. Inverse Stefan Problems. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5488-8.
Full textBeilina, Larisa, ed. Applied Inverse Problems. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7816-4.
Full textBook chapters on the topic "Inverse problems"
Richter, Mathias. "Characterization of Inverse Problems." In Inverse Problems, 1–28. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_1.
Full textRichter, Mathias. "Discretization of Inverse Problems." In Inverse Problems, 29–75. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_2.
Full textRichter, Mathias. "Regularization of Linear Inverse Problems." In Inverse Problems, 77–155. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_3.
Full textRichter, Mathias. "Regularization of Nonlinear Inverse Problems." In Inverse Problems, 157–93. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48384-9_4.
Full textRichter, Mathias. "Characterization of Inverse Problems." In Inverse Problems, 1–29. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_1.
Full textRichter, Mathias. "Discretization of Inverse Problems." In Inverse Problems, 31–83. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_2.
Full textRichter, Mathias. "Regularization of Linear Inverse Problems." In Inverse Problems, 85–163. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_3.
Full textRichter, Mathias. "Regularization of Nonlinear Inverse Problems." In Inverse Problems, 165–212. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59317-9_4.
Full textAnderssen, R. S. "The Linear Functional Strategy for Improperly Posed Problems." In Inverse Problems, 11–30. Basel: Birkhäuser Basel, 1986. http://dx.doi.org/10.1007/978-3-0348-7014-6_1.
Full textCannon, John R., and Salvador Pérez Esteva. "A Note on an Inverse Problem Related to the 3-D Heat Equation." In Inverse Problems, 133–37. Basel: Birkhäuser Basel, 1986. http://dx.doi.org/10.1007/978-3-0348-7014-6_10.
Full textConference papers on the topic "Inverse problems"
Zhdanov, Michael. "Electromagnetic Inverse Problems." In 5th International Congress of the Brazilian Geophysical Society. European Association of Geoscientists & Engineers, 1997. http://dx.doi.org/10.3997/2214-4609-pdb.299.202.
Full textBaltes, H. P. "Inverse grating problems." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1985. http://dx.doi.org/10.1364/oam.1985.thd2.
Full textSnieder, Roel. "Inverse Problems in Geophysics." In Signal Recovery and Synthesis. Washington, D.C.: OSA, 2001. http://dx.doi.org/10.1364/srs.2001.sma2.
Full text"Inverse Problems and Synthesis." In 2018 XXIIIrd International Seminar/Workshop on Direct and Inverse Problems of Electromagnetic and Acoustic Wave Theory (DIPED). IEEE, 2018. http://dx.doi.org/10.1109/diped.2018.8543271.
Full textJaeaeskelaeinen, Timo, and Markku Kuittinen. "Inverse grating diffraction problems." In Szklarska - DL tentative, edited by Jerzy Nowak and Marek Zajac. SPIE, 1991. http://dx.doi.org/10.1117/12.50118.
Full text"Inverse and Optimization Problems." In 10th International Conference on Mathematical Methods in Electromagnetic Theory, 2004. IEEE, 2004. http://dx.doi.org/10.1109/mmet.2004.1397075.
Full text"Inverse & nonlinear problems." In 2008 12th International Conference on Mathematical Methods in Electromagnetic Theory. IEEE, 2008. http://dx.doi.org/10.1109/mmet.2008.4580915.
Full textTuncer, E. "Inverse problems in dielectrics." In 2011 IEEE 14th International Symposium on Electrets ISE 14. IEEE, 2011. http://dx.doi.org/10.1109/ise.2011.6084990.
Full textGOYAL, KAVITA, and MANI MEHRA. "WAVELETS AND INVERSE PROBLEMS." In Proceedings of the Satellite Conference of ICM 2010. WORLD SCIENTIFIC, 2011. http://dx.doi.org/10.1142/9789814338820_0015.
Full textShinohara, Masaaki. "Inverse Problems in AHP." In International Symposium on the Analytic Hierarchy Process. Creative Decisions Foundation, 2014. http://dx.doi.org/10.13033/isahp.y2014.112.
Full textReports on the topic "Inverse problems"
Santosa, Fadil. Inverse Problems in Nondestructive Evaluations. Fort Belvoir, VA: Defense Technical Information Center, August 1992. http://dx.doi.org/10.21236/ada261370.
Full textFriedman, Avner. Inverse Problems in Wave Propagation. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada302229.
Full textBarhen, J., J. G. Berryman, L. Borcea, J. Dennis, C. de Groot-Hedlin, F. Gilbert, P. Gill, et al. Optimization and geophysical inverse problems. Office of Scientific and Technical Information (OSTI), October 2000. http://dx.doi.org/10.2172/939130.
Full textAngell, T. S., and R. E. Kleinman. Inverse and Control Problems in Electromagnetics. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada292993.
Full textGordon, Howard R. Inverse Problems in Hydrologic Radiative Transfer. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada629879.
Full textColton, David, and Peter Monk. Inverse Scattering Problems for Electromagnetic Waves. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada337286.
Full textMichalski, Anatoli I. Inverse problems in demography and biodemography. Rostock: Max Planck Institute for Demographic Research, November 2006. http://dx.doi.org/10.4054/mpidr-wp-2006-041.
Full textHorowitz, Joel L. Ill-posed inverse problems in economics. Institute for Fiscal Studies, August 2013. http://dx.doi.org/10.1920/wp.cem.2013.3713.
Full textGordon, Howard R. Inverse Problems in Hydrologic Radiative Transfer. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada626577.
Full textWolf, Emil. Direct and Inverse Problems in Statistical Wavefields. Office of Scientific and Technical Information (OSTI), September 2002. http://dx.doi.org/10.2172/900275.
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