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Biblioteca

MARC Lista (tabellare)
Applied inverse problems : lectures presented at the RCP 264, "Etude interdisciplinaire des problèmes inverses" / sponsored by the Centre National de la Recherche Scientifique ; edited by P. C. Sabatier
Applied inverse problems : lectures presented at the RCP 264, "Etude interdisciplinaire des problèmes inverses" / sponsored by the Centre National de la Recherche Scientifique ; edited by P. C. Sabatier
Autore Centre National de la Recherche Scientifique (France)
Pubbl/distr/stampa Berlin : Springer, 1978
Descrizione fisica v, 425 p. : ill. ; 25 cm
Disciplina 530.1/5/535
Altri autori (Persone) Sabatier, Pierre Celestin
Collana Lecture notes in physics / edited by J. Ehlers...[et al.] ; 85
Soggetto topico Inverse problems (Differential equations)
Mathematical physics
Geophysics - Mathematics
Classificazione LC QC20.7.D5
510.35
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991000816359707536
Centre National de la Recherche Scientifique (France)  
Berlin : Springer, 1978
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Applied inverse problems : select contributions from the first Annual Workshop on Inverse Problems / / Larisa Beilina, editor
Applied inverse problems : select contributions from the first Annual Workshop on Inverse Problems / / Larisa Beilina, editor
Edizione [1st ed. 2013.]
Pubbl/distr/stampa New York : , : Springer, , 2013
Descrizione fisica 1 online resource (xiii, 197 pages) : illustrations (chiefly color)
Disciplina 515.35
530.15537
Collana Springer Proceedings in Mathematics & Statistics
Soggetto topico Inverse problems (Differential equations)
Mathematical physics
Geophysics
ISBN 1-4614-7816-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Theoretical and Numerical Study of Iteratively Truncated Newton's Algorithm, Anatoly B. Bakushinsky, Alexandra B. Smirnova, and Hui Liu -- Approximate Global Convergence in Imaging of Land Mines from Backscattered Data, L. Beilina and M. V. Klibanov -- Time-adaptive FEM for Distributed Parameter Identification in Biological Models, L. Beilina and I.Gainova -- Adaptive finite element method in reconstruction of dielectrics from backscattered data, L. Beilina, M. P. Hatlo Andresen, H. E. Krogstad -- A Posteriori Error Estimates for Fredholm Integral Equations of the First Kind, N. Koshev and L. Beilina.- Inverse Problems in Geomechanics: Diagnostics and Prediction of the State of Rock Masses with Estimating Their Properties, L. A. Nazarova and L.A. Nazarov --  A Globally Convergent Numerical Method for Coefficient Inverse Problems with Time-Dependent Data, Aubrey Rhoden, Natee Patong, Yueming Liu, Jianzhong Su and Hanli Liu -- Adaptive FEM with relaxation for a hyperbolic coefficient inverse problem, L. Beilina and M. V. Klibanov -- Error Estimation in Ill-posed Problems in Special Cases, A. G. Yagola, Y. M. Korolev.-  Stable numerical methods of approaching quantum mechanical molecular force fields to experimental data, G. Kuramshina, I. Kochikov and A. Yagola -- On the Alternating Method for Cauchy Problems and its Finite Element Discretisation, Thouraya N. Baranger B. Tomas Johansson and Romain Rischette.
Record Nr. UNINA-9910438140203321
New York : , : Springer, , 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Basic methods of tomography and inverse problems : a set of lectures by G.T. Herman, H.K. Tuy, K.J. Langenberg and P.C. Sabatier / edited by P.C. Sabatier
Basic methods of tomography and inverse problems : a set of lectures by G.T. Herman, H.K. Tuy, K.J. Langenberg and P.C. Sabatier / edited by P.C. Sabatier
Autore Sabatier, Pierre Celestin
Edizione [1st ed]
Pubbl/distr/stampa Bristol : Adam Hilger Ltd, c1987
Descrizione fisica xii, 671 p. : ill. ; 24 cm.
Collana Malvern Physics Series / E.R. Pike ; 4
Soggetto topico Inverse problems (Differential equations)
Tomography
ISBN 0852744757
Classificazione 53.2.24
53.2.46
53.9.7
510.34
510.42
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISALENTO-991000833799707536
Sabatier, Pierre Celestin  
Bristol : Adam Hilger Ltd, c1987
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Bayesian approach to inverse problems [[electronic resource] /] / edited by Jerome Idier
Bayesian approach to inverse problems [[electronic resource] /] / edited by Jerome Idier
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (383 p.)
Disciplina 515/.357
519.542
Altri autori (Persone) IdierJérôme
Collana Digital signal and image processing series.
Soggetto topico Inverse problems (Differential equations)
Bayesian statistical decision theory
ISBN 1-282-16506-2
9786612165061
0-470-61119-7
0-470-39382-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Bayesian Approach to Inverse Problems; Table of Contents; Introduction; Part I. Fundamental Problems and Tools; Chapter 1. Inverse Problems, Ill-posed Problems; 1.1. Introduction; 1.2. Basic example; 1.3. Ill-posed problem; 1.3.1. Case of discrete data; 1.3.2. Continuous case; 1.4. Generalized inversion; 1.4.1. Pseudo-solutions; 1.4.2. Generalized solutions; 1.4.3. Example; 1.5. Discretization and conditioning; 1.6. Conclusion; 1.7. Bibliography; Chapter 2. Main Approaches to the Regularization of Ill-posed Problems; 2.1. Regularization; 2.1.1. Dimensionality control
2.1.1.1. Truncated singular value decomposition2.1.1.2. Change of discretization; 2.1.1.3. Iterative methods; 2.1.2. Minimization of a composite criterion; 2.1.2.1. Euclidian distances; 2.1.2.2. Roughness measures; 2.1.2.3. Non-quadratic penalization; 2.1.2.4. Kullback pseudo-distance; 2.2. Criterion descent methods; 2.2.1. Criterion minimization for inversion; 2.2.2. The quadratic case; 2.2.2.1. Non-iterative techniques; 2.2.2.2. Iterative techniques; 2.2.3. The convex case; 2.2.4. General case; 2.3. Choice of regularization coefficient; 2.3.1. Residual error energy control
2.3.2. "L-curve" method2.3.3. Cross-validation; 2.4. Bibliography; Chapter 3. Inversion within the Probabilistic Framework; 3.1. Inversion and inference; 3.2. Statistical inference; 3.2.1. Noise law and direct distribution for data; 3.2.2. Maximum likelihood estimation; 3.3. Bayesian approach to inversion; 3.4. Links with deterministic methods; 3.5. Choice of hyperparameters; 3.6. A priori model; 3.7. Choice of criteria; 3.8. The linear, Gaussian case; 3.8.1. Statistical properties of the solution; 3.8.2. Calculation of marginal likelihood; 3.8.3. Wiener filtering; 3.9. Bibliography
Part II. DeconvolutionChapter 4. Inverse Filtering and Other Linear Methods; 4.1. Introduction; 4.2. Continuous-time deconvolution; 4.2.1. Inverse filtering; 4.2.2. Wiener filtering; 4.3. Discretization of the problem; 4.3.1. Choice of a quadrature method; 4.3.2. Structure of observation matrix H; 4.3.3. Usual boundary conditions; 4.3.4. Problem conditioning; 4.3.4.1. Case of the circulant matrix; 4.3.4.2. Case of the Toeplitz matrix; 4.3.4.3. Opposition between resolution and conditioning; 4.3.5. Generalized inversion; 4.4. Batch deconvolution; 4.4.1. Preliminary choices
4.4.2. Matrix form of the estimate4.4.3. Hunt's method (periodic boundary hypothesis); 4.4.4. Exact inversion methods in the stationary case; 4.4.5. Case of non-stationary signals; 4.4.6. Results and discussion on examples; 4.4.6.1. Compromise between bias and variance in 1D deconvolution; 4.4.6.2. Results for 2D processing; 4.5. Recursive deconvolution; 4.5.1. Kalman filtering; 4.5.2. Degenerate state model and recursive least squares; 4.5.3. Autoregressive state model; 4.5.3.1. Initialization; 4.5.3.2. Criterion minimized by Kalman smoother; 4.5.3.3. Example of result
4.5.4. Fast Kalman filtering
Record Nr. UNINA-9910139505603321
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bayesian approach to inverse problems [[electronic resource] /] / edited by Jerome Idier
Bayesian approach to inverse problems [[electronic resource] /] / edited by Jerome Idier
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (383 p.)
Disciplina 515/.357
519.542
Altri autori (Persone) IdierJérôme
Collana Digital signal and image processing series.
Soggetto topico Inverse problems (Differential equations)
Bayesian statistical decision theory
ISBN 1-282-16506-2
9786612165061
0-470-61119-7
0-470-39382-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Bayesian Approach to Inverse Problems; Table of Contents; Introduction; Part I. Fundamental Problems and Tools; Chapter 1. Inverse Problems, Ill-posed Problems; 1.1. Introduction; 1.2. Basic example; 1.3. Ill-posed problem; 1.3.1. Case of discrete data; 1.3.2. Continuous case; 1.4. Generalized inversion; 1.4.1. Pseudo-solutions; 1.4.2. Generalized solutions; 1.4.3. Example; 1.5. Discretization and conditioning; 1.6. Conclusion; 1.7. Bibliography; Chapter 2. Main Approaches to the Regularization of Ill-posed Problems; 2.1. Regularization; 2.1.1. Dimensionality control
2.1.1.1. Truncated singular value decomposition2.1.1.2. Change of discretization; 2.1.1.3. Iterative methods; 2.1.2. Minimization of a composite criterion; 2.1.2.1. Euclidian distances; 2.1.2.2. Roughness measures; 2.1.2.3. Non-quadratic penalization; 2.1.2.4. Kullback pseudo-distance; 2.2. Criterion descent methods; 2.2.1. Criterion minimization for inversion; 2.2.2. The quadratic case; 2.2.2.1. Non-iterative techniques; 2.2.2.2. Iterative techniques; 2.2.3. The convex case; 2.2.4. General case; 2.3. Choice of regularization coefficient; 2.3.1. Residual error energy control
2.3.2. "L-curve" method2.3.3. Cross-validation; 2.4. Bibliography; Chapter 3. Inversion within the Probabilistic Framework; 3.1. Inversion and inference; 3.2. Statistical inference; 3.2.1. Noise law and direct distribution for data; 3.2.2. Maximum likelihood estimation; 3.3. Bayesian approach to inversion; 3.4. Links with deterministic methods; 3.5. Choice of hyperparameters; 3.6. A priori model; 3.7. Choice of criteria; 3.8. The linear, Gaussian case; 3.8.1. Statistical properties of the solution; 3.8.2. Calculation of marginal likelihood; 3.8.3. Wiener filtering; 3.9. Bibliography
Part II. DeconvolutionChapter 4. Inverse Filtering and Other Linear Methods; 4.1. Introduction; 4.2. Continuous-time deconvolution; 4.2.1. Inverse filtering; 4.2.2. Wiener filtering; 4.3. Discretization of the problem; 4.3.1. Choice of a quadrature method; 4.3.2. Structure of observation matrix H; 4.3.3. Usual boundary conditions; 4.3.4. Problem conditioning; 4.3.4.1. Case of the circulant matrix; 4.3.4.2. Case of the Toeplitz matrix; 4.3.4.3. Opposition between resolution and conditioning; 4.3.5. Generalized inversion; 4.4. Batch deconvolution; 4.4.1. Preliminary choices
4.4.2. Matrix form of the estimate4.4.3. Hunt's method (periodic boundary hypothesis); 4.4.4. Exact inversion methods in the stationary case; 4.4.5. Case of non-stationary signals; 4.4.6. Results and discussion on examples; 4.4.6.1. Compromise between bias and variance in 1D deconvolution; 4.4.6.2. Results for 2D processing; 4.5. Recursive deconvolution; 4.5.1. Kalman filtering; 4.5.2. Degenerate state model and recursive least squares; 4.5.3. Autoregressive state model; 4.5.3.1. Initialization; 4.5.3.2. Criterion minimized by Kalman smoother; 4.5.3.3. Example of result
4.5.4. Fast Kalman filtering
Record Nr. UNINA-9910830737403321
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bayesian approach to inverse problems [[electronic resource] /] / edited by Jerome Idier
Bayesian approach to inverse problems [[electronic resource] /] / edited by Jerome Idier
Pubbl/distr/stampa London, : ISTE
Descrizione fisica 1 online resource (383 p.)
Disciplina 515/.357
519.542
Altri autori (Persone) IdierJérôme
Collana Digital signal and image processing series.
Soggetto topico Inverse problems (Differential equations)
Bayesian statistical decision theory
ISBN 1-282-16506-2
9786612165061
0-470-61119-7
0-470-39382-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Bayesian Approach to Inverse Problems; Table of Contents; Introduction; Part I. Fundamental Problems and Tools; Chapter 1. Inverse Problems, Ill-posed Problems; 1.1. Introduction; 1.2. Basic example; 1.3. Ill-posed problem; 1.3.1. Case of discrete data; 1.3.2. Continuous case; 1.4. Generalized inversion; 1.4.1. Pseudo-solutions; 1.4.2. Generalized solutions; 1.4.3. Example; 1.5. Discretization and conditioning; 1.6. Conclusion; 1.7. Bibliography; Chapter 2. Main Approaches to the Regularization of Ill-posed Problems; 2.1. Regularization; 2.1.1. Dimensionality control
2.1.1.1. Truncated singular value decomposition2.1.1.2. Change of discretization; 2.1.1.3. Iterative methods; 2.1.2. Minimization of a composite criterion; 2.1.2.1. Euclidian distances; 2.1.2.2. Roughness measures; 2.1.2.3. Non-quadratic penalization; 2.1.2.4. Kullback pseudo-distance; 2.2. Criterion descent methods; 2.2.1. Criterion minimization for inversion; 2.2.2. The quadratic case; 2.2.2.1. Non-iterative techniques; 2.2.2.2. Iterative techniques; 2.2.3. The convex case; 2.2.4. General case; 2.3. Choice of regularization coefficient; 2.3.1. Residual error energy control
2.3.2. "L-curve" method2.3.3. Cross-validation; 2.4. Bibliography; Chapter 3. Inversion within the Probabilistic Framework; 3.1. Inversion and inference; 3.2. Statistical inference; 3.2.1. Noise law and direct distribution for data; 3.2.2. Maximum likelihood estimation; 3.3. Bayesian approach to inversion; 3.4. Links with deterministic methods; 3.5. Choice of hyperparameters; 3.6. A priori model; 3.7. Choice of criteria; 3.8. The linear, Gaussian case; 3.8.1. Statistical properties of the solution; 3.8.2. Calculation of marginal likelihood; 3.8.3. Wiener filtering; 3.9. Bibliography
Part II. DeconvolutionChapter 4. Inverse Filtering and Other Linear Methods; 4.1. Introduction; 4.2. Continuous-time deconvolution; 4.2.1. Inverse filtering; 4.2.2. Wiener filtering; 4.3. Discretization of the problem; 4.3.1. Choice of a quadrature method; 4.3.2. Structure of observation matrix H; 4.3.3. Usual boundary conditions; 4.3.4. Problem conditioning; 4.3.4.1. Case of the circulant matrix; 4.3.4.2. Case of the Toeplitz matrix; 4.3.4.3. Opposition between resolution and conditioning; 4.3.5. Generalized inversion; 4.4. Batch deconvolution; 4.4.1. Preliminary choices
4.4.2. Matrix form of the estimate4.4.3. Hunt's method (periodic boundary hypothesis); 4.4.4. Exact inversion methods in the stationary case; 4.4.5. Case of non-stationary signals; 4.4.6. Results and discussion on examples; 4.4.6.1. Compromise between bias and variance in 1D deconvolution; 4.4.6.2. Results for 2D processing; 4.5. Recursive deconvolution; 4.5.1. Kalman filtering; 4.5.2. Degenerate state model and recursive least squares; 4.5.3. Autoregressive state model; 4.5.3.1. Initialization; 4.5.3.2. Criterion minimized by Kalman smoother; 4.5.3.3. Example of result
4.5.4. Fast Kalman filtering
Record Nr. UNINA-9910840962503321
London, : ISTE
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Complex Datasets and Inverse Problems: Tomography, Networks and Beyond
Complex Datasets and Inverse Problems: Tomography, Networks and Beyond
Pubbl/distr/stampa [Place of publication not identified], : Institute of Mathematical Statistics, 2007
Descrizione fisica 1 online resource (viii, 273 pages) : illustrations
Disciplina 515.357
Collana Lecture notes-monograph series
Soggetto topico Inverse problems (Differential equations)
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deconvolution by simulation -- An iterative tomogravity algorithm for the estimation of network traffic -- Statistical inverse problems in active network tomography -- Network tomography based on 1-D projections -- Using data network metrics, graphics, and topology to explore network characteristics -- A flexible Bayesian generalized linear model for dichotomous response data with an application to text categorization -- Estimating the proportion of differentially expressed genes in comparative DNA microarray experiments -- Functional analysis via extensions of the band depth -- A representative sampling plan for auditing health insurance claims -- Confidence distribution (CD) -- distribution estimator of a parameter -- Empirical Bayes methods for controlling the false discovery rate with dependent data -- A smoothing model for sample disclosure risk estimation -- A note on the U, V method of estimation -- Local polynomial regression on unknown manifolds -- Shape restricted regression with random Bernstein polynomials -- Non- and semi-parametric analysis of failure time data with missing failure indicators -- Nonparametric estimation of a distribution function under biased sampling and censoring -- Estimating a Polya frequency function 2 -- A comparison of the accuracy of saddlepoint conditional cumulative distribution function approximations -- Multivariate medians and measure-symmetrization -- Statistical thinking: From Tukey to Vardi and beyond.
Record Nr. UNINA-9910482889403321
[Place of publication not identified], : Institute of Mathematical Statistics, 2007
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Complex Datasets and Inverse Problems: Tomography, Networks and Beyond
Complex Datasets and Inverse Problems: Tomography, Networks and Beyond
Pubbl/distr/stampa [Place of publication not identified], : Institute of Mathematical Statistics, 2007
Descrizione fisica 1 online resource (viii, 273 pages) : illustrations
Disciplina 515.357
Collana Lecture notes-monograph series
Soggetto topico Inverse problems (Differential equations)
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Deconvolution by simulation -- An iterative tomogravity algorithm for the estimation of network traffic -- Statistical inverse problems in active network tomography -- Network tomography based on 1-D projections -- Using data network metrics, graphics, and topology to explore network characteristics -- A flexible Bayesian generalized linear model for dichotomous response data with an application to text categorization -- Estimating the proportion of differentially expressed genes in comparative DNA microarray experiments -- Functional analysis via extensions of the band depth -- A representative sampling plan for auditing health insurance claims -- Confidence distribution (CD) -- distribution estimator of a parameter -- Empirical Bayes methods for controlling the false discovery rate with dependent data -- A smoothing model for sample disclosure risk estimation -- A note on the U, V method of estimation -- Local polynomial regression on unknown manifolds -- Shape restricted regression with random Bernstein polynomials -- Non- and semi-parametric analysis of failure time data with missing failure indicators -- Nonparametric estimation of a distribution function under biased sampling and censoring -- Estimating a Polya frequency function 2 -- A comparison of the accuracy of saddlepoint conditional cumulative distribution function approximations -- Multivariate medians and measure-symmetrization -- Statistical thinking: From Tukey to Vardi and beyond.
Record Nr. UNISA-996210067603316
[Place of publication not identified], : Institute of Mathematical Statistics, 2007
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Complex Webs : Anticipating the Improbable / Bruce J. West, Paolo Grigolini
Complex Webs : Anticipating the Improbable / Bruce J. West, Paolo Grigolini
Autore West, Bruce J.
Pubbl/distr/stampa Cambridge : Cambridge University Press, c2011
Descrizione fisica x, 375 p. : ill. ; 26 cm
Disciplina 003.72
Altri autori (Persone) Grigolini, Paolo, 1940-author
Soggetto topico Dynamics - Statistical methods
Inverse relationships (Mathematics)
Inverse problems (Differential equations)
ISBN 9780521113663
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface; 1. Webs; 2. Webs, trees and branches; 3. Mostly linear dynamics; 4. Random walks and chaos; 5. Non-analytic dynamics; 6. Brief recent history of webs; 7. Dynamics of chance; 8. Synopsis.
Record Nr. UNISALENTO-991003599029707536
West, Bruce J.  
Cambridge : Cambridge University Press, c2011
Materiale a stampa
Lo trovi qui: Univ. del Salento
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Composite type equations and inverse problems / / A.I. Kozhanov
Composite type equations and inverse problems / / A.I. Kozhanov
Autore Kozhanov A. I.
Edizione [Reprint 2014]
Pubbl/distr/stampa Utrecht, the Netherlands : , : VSP, , 1999
Descrizione fisica 1 online resource (181 pages)
Collana Inverse and ill-posed problems series
Soggetto topico Boundary value problems
Differential equations, Partial
Inverse problems (Differential equations)
Soggetto genere / forma Electronic books.
ISBN 3-11-094327-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface -- Introduction -- Chapter 1. Composite type equations as the original mathematical object -- Chapter 2. Solvability of inverse problems and other applications -- Conclusion -- Bibliography
Record Nr. UNINA-9910463704803321
Kozhanov A. I.  
Utrecht, the Netherlands : , : VSP, , 1999
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui