TY - BOOK
ID - 5360853
TI - Rank-deficient and discrete ill-posed problems : numerical aspects of linear inversion
PY - 1998
SN - 9780898714036 0898714036
PB - Philadelphia (Pa.): SIAM
DB - UniCat
KW - Equations, Simultaneous
KW - Iterative methods (Mathematics)
KW - Sparse matrices.
KW - Itération (Mathématiques)
KW - Matrices éparses
KW - Numerical solutions.
KW - 519.6
KW - 681.3*G13
KW - 517.95
KW - #TELE:SISTA
KW - 681.3*G15
KW - Computational mathematics. Numerical analysis. Computer programming
KW - Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems
KW - Partial differential equations
KW - Roots of nonlinear equations: convergence; error analysis; iterative methods;polynomials (Numerical analysis)
KW - 681.3*G15 Roots of nonlinear equations: convergence; error analysis; iterative methods;polynomials (Numerical analysis)
KW - 517.95 Partial differential equations
KW - 681.3*G13 Numerical linear algebra: conditioning; determinants; Eigenvalues; error analysis; linear systems; matrix inversion; pseudoinverses; sparse and very largesystems
KW - 519.6 Computational mathematics. Numerical analysis. Computer programming
KW - Iterative methods (Mathematics).
KW - Itération (Mathématiques)
KW - Matrices éparses
KW - Sparse matrices
KW - Spare matrix techniques
KW - Matrices
KW - Iteration (Mathematics)
KW - Numerical analysis
KW - Numerical solutions
UR - https://www.unicat.be/uniCat?func=search&query=sysid:5360853
AB - Here is an overview of modern computational stabilization methods for linear inversion, with applications to a variety of problems in audio processing, medical imaging, seismology, astronomy, and other areas. Rank-deficient problems involve matrices that are exactly or nearly rank deficient. Such problems often arise in connection with noise suppression and other problems where the goal is to suppress unwanted disturbances of given measurements. Discrete ill-posed problems arise in connection with the numerical treatment of inverse problems, where one typically wants to compute information about interior properties using exterior measurements. Examples of inverse problems are image restoration and tomography, where one needs to improve blurred images or reconstruct pictures from raw data. This book describes new and existing numerical methods for the analysis and solution of rank-deficient and discrete ill-posed problems. The emphasis is on insight into the stabilizing properties of the algorithms and the efficiency and reliability of the computations.
ER -