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Nonlinear Least Squares for Inverse Problems

Presents an introduction into the least squares resolution of nonlinear inverse problems. This title intends to develop a geometrical theory to analyze nonlinear least square (NLS) problems with respect to their quadratic wellposedness, that is, both wellposedness and optimizability

Detalles Bibliográficos
Autor principal: Chavent, Guy
Lenguaje:eng
Publicado: Springer 2009
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-90-481-2785-6
http://cds.cern.ch/record/1315461
Descripción
Sumario:Presents an introduction into the least squares resolution of nonlinear inverse problems. This title intends to develop a geometrical theory to analyze nonlinear least square (NLS) problems with respect to their quadratic wellposedness, that is, both wellposedness and optimizability