| 1 | Introduction | 1 |
| 1.1 | Direct and Inverse Problems | 1 |
| 1.1.1 | Two Broad Divisions of Inverse Problems | 2 |
| 1.2 | The Basic Concepts | 8 |
| 1.2.1 | The Approximate Nature of an Inverse Solution | 8 |
| 1.2.2 | The Smoothing Action Of An Integral Operator | 10 |
| 1.2.3 | The Role of a priori Knowledge | 12 |
| 1.2.4 | Ill- and Well-posed Problems | 13 |
| 2 | Some Examples of Ill-posed Problems | 17 |
| 2.1 | Introduction | 17 |
| 2.2 | Examples | 17 |
| 2.2.1 | Example 1. The Cauchy Problem for the Backward Heat Equation | 17 |
| 2.2.2 | Example 2. The Cauchy Problem for the Laplace Equation | 21 |
| 2.2.3 | Example 3. The Laplace Transform | 23 |
| 2.2.4 | Example 4. Numerical Differentiation | 28 |
| 2.2.5 | Example 5. Inverse Source Problem | 32 |
| Inverse Diffraction and Near-Field Holography | 36 |
| 2.2.6 | Example 6. An Example from Medical Diagnostics | 40 |
| 2.2.7 | Example 7. A Nonlinear Problem | 44 |
| 3 | Theory of Ill-posed Problems | 49 |
| 3.1 | Introduction | 49 |
| 3.2 | Tikhonov's Theorem | 51 |
| 3.3 | Regularization on a Compactum: The Quasisolution | 54 |
| 3.4 | Generalized Solutions | 56 |
| 3.4.1 | Summary | 62 |
| 3.4.2 | Connection with Quasisolution | 63 |
| 3.5 | Singular Value Expansion | 63 |
| 3.6 | Tikhonov's Theory of Regularization | 68 |
| 3.6.1 | The Regularizing Operator | 70 |
| The [epsilon]--[delta] Definition | 70 |
| The Parametric Definition | 71 |
| 3.6.2 | The Construction of Regularizers | 74 |
| 3.6.3 | The Spectral or Filter Functions | 78 |
| The Iterative Filters | 79 |
| 3.6.4 | First-order regularization | 82 |
| 3.7 | Convergence, Stability and Optimality | 85 |
| 3.7.1 | Convergence and Stability Estimates | 85 |
| 3.7.2 | The Optimality of a Regularization Strategy | 87 |
| 3.8 | The Determination of [alpha] | 90 |
| 3.8.1 | The Existence of an Optimal Value of [alpha] | 90 |
| 3.8.2 | The Discrepancy Principle | 93 |
| 3.9 | An Application | 96 |
| 3.10 | The Method of Mollification | 97 |
| 3.10.1 | The Method | 97 |
| 3.10.2 | An Example: Numerical Differentiation | 102 |
| 4 | Regularization by Projections | 105 |
| 4.1 | Introduction | 105 |
| 4.2 | The Basic Projection Methods | 105 |
| 4.3 | The Method of Projections: General Framework | 108 |
| 4.4 | The Method of Least-Square | 113 |
| 4.5 | The Method of Collocation | 117 |
| 4.6 | The Standard Galerkin Method | 120 |
| 4.6.1 | The Galerkin Approximation in one Dimension | 120 |
| 4.6.2 | The General Case | 125 |
| 4.6.3 | The Galerkin Method and FEM | 128 |
| 4.6.4 | The Perturbed Data | 130 |
| 4.6.5 | The Petrov-Galerkin Method | 131 |
| 5 | Discrete Ill-posed Problems | 133 |
| 5.1 | Introduction | 133 |
| 5.2 | Discrete Decompositions | 134 |
| 5.3 | The Discrete Tikhonov Regularization | 145 |
| 5.4 | An Example | 146 |
| 5.5 | Discrete Solution of a Tikhonov Functional | 150 |
| 5.6 | Appendix A.5.1 | 154 |
| 5.7 | Appendix A.5.2 | 159 |
| 5.8 | Appendix A.5.3 | 164 |
| 6 | The Helmholtz Scattering | 169 |
| 6.1 | Introduction | 169 |
| 6.2 | Gauss' or Divergence Theorem | 171 |
| 6.3 | Green's Identities | 173 |
| 6.4 | The Helmholtz Equation | 175 |
| 6.5 | The Helmholtz Representation in the Interior | 178 |
| 6.6 | The Radiation Condition | 180 |
| 6.7 | The Helmholtz Representation in the Exterior | 188 |
| 6.8 | Some Properties of the Scattering Solutions | 190 |
| 6.9 | The Helmholtz Scattering from Inhomogeneities | 193 |
| 7 | The Solutions | 203 |
| 7.1 | Introduction | 203 |
| 7.2 | The Layer Potentials | 204 |
| 7.3 | Replacing G[superscript 0] (x, y; k) by g[superscript 0] (x, y) | 206 |
| 7.4 | The Double-layer Potential | 211 |
| 7.5 | The Single-layer Potential | 216 |
| 7.6 | The Helmholtz Scattering Problems | 222 |
| 7.6.1 | The Dirichet and Neumann Obstacle Scattering | 222 |
| 7.7 | Unconditionally Unique Solution | 227 |
| 7.7.1 | Combining Single and Double-layer Potentials | 228 |
| 7.8 | The Transmission Problem | 234 |
| 7.9 | Jones' Method | 237 |
| 7.10 | Appendix A.7.1 | 239 |
| 7.11 | Appendix A.7.2 | 241 |
| 7.12 | Appendix A.7.3 | 242 |
| 7.13 | Appendix A.7.4 | 243 |
| 7.14 | Appendix A.7.5 | 245 |
| 7.15 | Appendix A.7.6 | 245 |
| 8 | Uniqueness Theorems in Inverse Problems | 247 |
| 8.1 | Some Definitions | 247 |
| 8.2 | Properties of the Total Fields | 249 |
| 8.2.1 | Obstacle Scattering: Linear Independence of Total Fields | 249 |
| 8.2.2 | Inhomogeneity Scattering | 250 |
| 8.3 | The Dirichlet and Neumann Spectrum | 253 |
| 8.3.1 | The Spectrum of the Negative of the Dirichlet Laplacian in a Bounded Domain | 253 |
| 8.3.2 | The Analysis of the Neumann Laplacian | 256 |
| 8.4 | The Uniqueness of the Inverse Dirichlet Obstacle Problem | 259 |
| 8.5 | The Uniqueness of Inverse Neumann Obstacle | 261 |
| 8.6 | Uniqueness in Inverse Transmission Obstacle | 267 |
| 8.7 | Uniqueness of Inverse Inhomogeneity Scattering | 269 |
| 8.8 | Appendix A.8.1 | 277 |
| 8.9 | Appendix A.8.2 | 281 |
| 9 | Some Algorithms | 283 |
| 9.1 | Introduction | 283 |
| 9.2 | The Method of Potentials | 286 |
| 9.3 | The Method of Superposition of Incident Fields | 287 |
| 9.4 | The Method of Wavefunction Expansion | 290 |
| 9.5 | The Method of Boundary Variation | 292 |
| 9.5.1 | Dirichlet and Neumann Problem In Two-dimension | 297 |
| 9.5.2 | Transmission Problem in Two-dimensions | 298 |
| 9.6 | Some Nonoptimizational Methods | 300 |
| 9.6.1 | The Method of Colton and Kirsch | 301 |
| 9.6.2 | The Method of Eigensystem of the Far-field Operator | 303 |
| 9.7 | Appendix A.9.1 | 305 |
| 9.8 | Appendix A.9.2 | 309 |
| 9.9 | Appendix A.9.3 | 311 |
| 10 | Bibliography | 315 |