Listing 1 - 4 of 4 |
Sort by
|
Choose an application
Algorithms. --- Versification. --- Iterative methods (Mathematics)
Choose an application
Nonlinear inverse problems appear in many applications, and typically they lead to mathematical models that are ill-posed, i.e., they are unstable under data perturbations. Those problems require a regularization, i.e., a special numerical treatment. This book presents regularization schemes which are based on iteration methods, e.g., nonlinear Landweber iteration, level set methods, multilevel methods and Newton type methods.
519.61 --- Numerical methods of algebra --- Differential equations, Partial --- Iterative methods (Mathematics) --- Improperly posed problems. --- Iterative methods (Mathematics). --- Differential equations, Partial -- Improperly posed problems. --- Mathematics. --- Calculus --- Mathematics --- Physical Sciences & Mathematics --- Improperly posed problems --- 519.61 Numerical methods of algebra --- Iteration (Mathematics) --- Improperly posed problems in partial differential equations --- Ill-posed problems --- Inkorrekt gestelltes Problem. --- Regularisierungsverfahren. --- Iteration. --- Nichtlineares inverses Problem. --- Numerical analysis --- Iterative Regularization. --- Nonlinear Ill-Posed Problems. --- Nonlinear Inverse Problems.
Choose an application
Recent results in local convergence and semi-local convergence analysis constitute a natural framework for the theoretical study of iterative methods. This monograph provides a comprehensive study of both basic theory and new results in the area. Each chapter contains new theoretical results and important applications in engineering, modeling dynamic economic systems, input-output systems, optimization problems, and nonlinear and linear differential equations. Several classes of operators are considered, including operators without Lipschitz continuous derivatives, operators with high order derivatives, and analytic operators. Each section is self-contained. Examples are used to illustrate the theory and exercises are included at the end of each chapter. The book assumes a basic background in linear algebra and numerical functional analysis. Graduate students and researchers will find this book useful. It may be used as a self-study reference or as a supplementary text for an advanced course in numerical functional analysis.
Convergence --- Iterative methods (Mathematics) --- Newton-Raphson method --- Convergence (Mathématiques) --- Itération (Mathématiques) --- Convergence. --- Iterative methods (Mathematics). --- Newton-Raphson method. --- Engineering & Applied Sciences --- Applied Mathematics --- Method, Newton-Raphson --- Method of tangents --- Newton approximation method --- Newton iterative process --- Newton method --- Newton-Raphson algorithm --- Newton-Raphson formula --- Newton-Raphson process --- Newton's approximation method --- Newton's method --- Quadratically convergent Newton-Raphson process --- Raphson method, Newton --- -Second-order Newton-Raphson process --- Iteration (Mathematics) --- Mathematics. --- Functional analysis. --- Computer mathematics. --- Numerical analysis. --- Numerical Analysis. --- Computational Mathematics and Numerical Analysis. --- Functional Analysis. --- Numerical analysis --- Functions --- Computer science --- Functional calculus --- Calculus of variations --- Functional equations --- Integral equations --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Mathematical analysis --- Mathematics
Choose an application
Parallel processing (Electronic computers) --- Parallel algorithms --- Computational grids (Computer systems) --- Iterative methods (Mathematics) --- Parallélisme (Informatique) --- Algorithmes parallèles --- Grilles informatiques --- Itération (Mathématiques) --- 681.3*G17 Ordinary differential equations: boundary value problems; convergence and stability; error analysis; initial value problems; multistep methods; single step methods; stiff equations (Numerical analysis) --- Ordinary differential equations: boundary value problems; convergence and stability; error analysis; initial value problems; multistep methods; single step methods; stiff equations (Numerical analysis) --- Numerical linear algebra: conditioning; determinants; eigenvalues and eigenvectors; error analysis; linear systems; matrix inversion; pseudoinverses; singular value decomposition; sparse, structured, and very large systems (direct and iterative methods) --- 519.61 --- 681.3*G13 --- 681.3*G17 --- Iteration (Mathematics) --- Numerical analysis --- Grid computing --- Grids, Computational (Computer systems) --- Computer systems --- Cyberinfrastructure --- High performance computing --- Multiprocessors --- Parallel programming (Computer science) --- Supercomputers --- Algorithms --- 519.61 Numerical methods of algebra --- Numerical methods of algebra
Listing 1 - 4 of 4 |
Sort by
|