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Tarantola A. — Inverse problem theory and methods for model parameter estimation
Tarantola A. — Inverse problem theory and methods for model parameter estimation



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Название: Inverse problem theory and methods for model parameter estimation

Автор: Tarantola A.

Аннотация:

The use of actual observations to infer the properties of a model is an inverse problem, which are often difficult as they may not have a unique solution. This book proposes a general approach that is valid for linear as well as for nonlinear problems. The philosophy is essentially probabilistic and allows the reader to understand the basic difficulties appearing in the resolution of inverse problems. The book attempts to explain how a method of acquisition of information can be applied to actual real-world problems, including many heuristic arguments. Prompted by recent developments in inverse theory, this text is a completely rewritten version of a 1987 book by the same author, and includes many algorithmic details for Monte Carlo methods, least-squares discrete problems, and least-squares problems involving functions. In addition, some notions are clarified, the role of optimization techniques is underplayed, and Monte Carlo methods are taken much more seriously.


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: 1

Год издания: 2004

Количество страниц: 352

Добавлена в каталог: 02.11.2010

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Instrument, with additive noise      26
Instrument, with known statistics      25
Integral operator      184
Intersection      6
Intersection, of fuzzy sets      14
Invariance homogeneous probability density      11
Inverse      230
Inverse, modeling      2
Inverse, of a partitioned matrix      250
Inverse, of the covariance      188
Inverse, problem (solution)      32 33
Inversion sampling method      48
Inversion, of acoustic waveforms      297
Inversion, of elastic waveforms      144
Isometric isomorphism      241
Isomorphic, linear spaces      238
Isomorphic, spaces      231
Isomorphism      231 238
Isomorphism, isometric      241
Jacobian rule      8
Jaynes      6 11 163
Jeffreys      6 12 101 162
Jeffreys, parameter      12 162
Jeffreys, parameter (power)      163
Jeffreys, tensor      165
Jeroslow      225
Joint probability density      19
Journel      14 30
K6nig      225
Kalman filter      67 198
Kalos      42
Karal      300
Karmarkar      225
Keilis — Borok      42
Kernel      238
Kernel, operator      184
Kernel, subspace      184
Kirkpatrick      54
Klee      225
Kolmogorov axioms      6
Koren      47
Kupferschmid      225
Lagrange parameters      73 249
Landa      38
Landau      145
Lang      2
Laplace      xii 64 81
Laplace distribution      89
Laplace function      81
Large residuals      74
Laws physical      2
Lay      109
Least squares      57 62
Least squares, function      64
Least squares, norm      236
Least-absolute-values criterion      81 89
Lee      72
legendre      xii
Levenberg      80
Levenberg — Marquardt      80
Lifshitz      145
Likelihood      12
Likelihood, function      34 35 39
Linear      231
Linear, form      58 239
Linear, operator      237
Linear, operator (continuous)      241
Linear, problem      64
Linear, programming      95 223
Linear, programming (dual problems)      225
Linear, programming (ti-aorm)      228
Linear, regression (uncertainties in both axes)      273
Linear, regression (usual least-squares)      269
Linear, regression (with an outlier)      275 295
Linear, regression (with rounding errors)      266
Linear, space      58 234
Linear, space (normed)      183
Linear, subspace      236
Linearly independent      236
Lions      190
Local optimum      69
Log-normal probability density      175
Long-tailed distribution      81
Lovasc      225
Luenberger      95
Magnanti      95 225
Mangasarian      225
Manifold      2 232
Mapping      230
Marginal probability density      18
Marginalizing in linear least squares      200
Markov chain Monte Carlo      50
Marquardt      80
Mass of Earth's core      9
Math optimizer (software)      80
Mathematica      80
Mathematical expectation      171 172
MATLAB      80
Matrix identities      249
Maximum entropy probability density      245
Maximum likelihood point      39
McCall      225
MCMC      50
Mean      171 172
Mean, deviation      89 171 174
Mean, sample      162
Mean, value (of a random function)      105
Measure      6
Measure, density      7
Measurement uncertainties      21
Measurements      24
Measuring travel times      25
Median      171
Metric, on a manifold      160
Metric, open subset      234
Metric, space      183 232
Metropolis      50
Metropolis — Hastings algorithm      50
Metropolis, algorithm      41 50
Metropolis, algorithm (cascaded)      51
Midrange      171 175
Mille-feuille      58 206
Minimax, criterion      98
Minimax, norm      98
Minty      225
Misfit function, for nonlinear least-squares      68
Misfit function, in ${l}_{p}$-norm problems      88
Misfit function, in least-squares      64
Model      3
Model parameters a priori information      27
Model space, finite-dimensional      3
Model space, linear      4
Model space, manifold      2
Model space, random exploration      38
Model, parameters      1
Modelization, imperfections      21
Modelization, uncertainties (negligible)      34
Models, multiplication      4
Models, sum      4
Monte Carlo method of numerical integration      179
Monte Carlo methods      41
Morgan      37
Moritz      101
Morse      145 190
Mosegaard      19 22 35 50 51 53
Movie strategy      44
Muir      81 82 96
Murray      203
Murty      95
Narasimhan      2
Nash      225
Natural topology      234
Nazareth      225
Neglecting covariances      31
Negligible, modelization uncertainties      34
Negligible, observational uncertainties      35
Neighborhood      231
NEP      12
Nercessian      144 289
Neumann series      238
Newton, algorithm      211
Newton, method      76 210
Newton, method (for ${l}_{p}$-norms)      210
Noise additive      26
Noninformative probability density      11
Nonlinear least-squares      68
Nonlinear problem      64
Nonlinear regression      256
Norm      61 117 183 235
Norm, associated with exponential 3D covariance      313
Norm, associated with exponential covariance      308
Norm, associated with random walk      311
Norm, of a continuous operator      238
Norm, of the generalized Gaussian      250
Norm, of the gradient      209
Norm, properties      83
Norm, triangular      14
Normed linear space      235
Null space      184 238
Number, of iterations      69
Number, of parameters resolved      73
Objective function      64
Observable parameters      2
Observational uncertainties negligible      35
One-to-one      230
Onto      230
Open subset      231
Operator      230
Outlier      26 81
Outlier (example in geodetic adjustment)      296
Overdetermined      67
p-event      16
Pallaschke      225
Parameter manifold      6
Parameterization      1 2
Parameterization, equivalent      2
Parameterization, of a system      2
Parameters      6
Partial derivatives      68
Partition of data into subsets      197
Partitioned matrix inverse      250
Perfect information      9
Petrophysical parameters      24
Phillips      230
Physical, dimensions of a probability density      8
Physical, laws      2
Physical, system      1
Plackett      68
Point      232
Poisson ratio      163 166
Poisson ratio, homogeneous probability density      167
Poisson ratio, negative values      167
Polak      217
Popper      20
Positive definite bilinear form      240
Posterior covariance      66 70
Powell      203 217 219 220
Pre-Hilbert space      241
Preconditioned, gradient methods      78
Preconditioned, steepest descent      214
Prescribed covariance      116
Press      42
Principal components of the gradient      94
Prior probability density      32
probability      6
probability density      5 7 159
Probability density, a priori      32
Probability density, conditional      19
Probability density, homogeneous      7 10
Probability density, joint      19
Probability density, marginal      18
Probability density, noninformative      11
Probability density, physical dimensions      8
Probability density, theoretical      32
probability distribution      4
Probability, density      7
Probability, distribution      6
Probability, of causes      18
Probability, relative      7
Probability, volumetric      8
Probability-event      16
Product of probability densities      285
Pugachev      61 103 107 111 172
Quasi-Newton, algorithm      79
Quasi-Newton, in least squares      78
Quasi-Newton, method      69 215
Random exploration of the model space      38
Random walk, covariance function      114
Random walk, norm      311
Random, function      101
Random, function (characterization)      102
Random, function (realization)      111
Random, variable      9
Random, walk      52 102
RANGE      230
Rank of a linear operator      238
Rao      68 177
Rauhala      4
Reciprocity      146
Reeves      217
Reflexive space      239
Refutation of a theory      20
Rejection sampling method      49
Relative information (of two Gaussians)      201
Residuals large      74
Resolution operator      72
Resolving kernel      192
Ribiere      217
Richards      145 146
Riesz representation theorem      109 241
Rietsch      11 163
Roach      145
Roberts      229
Robust method      81
Rodgers      216
Rosenbrock function      204
Rothman      42 54
Roughing operator      61
Rounding error      81
Ruffle      41
Sample      6 34
Sampling, methods      48
Sampling, the posterior probability distribution      52
Sampling, the prior probability distribution      52
Savage      11
Scalar product      60 117 241 243
Scales      203 217 219
Schmitt      37
Schweizer      14
Self-adjoint      188
Self-adjoint operator      62
Self-adjoint, wave equation operator      190
Seneta      42
Sequential random realization      181
Sequential realization method      49
Series development      204
Shannon      12 220
shear modulus      11 165
Simplex method      95 96 223
Simplex method, example      293
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