The book provides a concise introduction into inverse modeling, i.e the theory and methods of inverse problems and data assimilation.Inverse problems are widely spread today in science and technology, ranging from data analysis and modeling in science to remotesensing in industrial and natural applications as well as medical imaging and nondestructive testing. Further applications come from thedata assimilation task, i.e. the use of inverse methods to control dynamical systems and provide initial states for forecasting, which is ofcentral importance in weather and climate science and an emerging technique in neuroscience and medicine.
The book provides a concise introduction into inverse modeling, i.e the theory and methods of inverse problems and data assimilation.Inverse problems are widely spread today in science and technology, ranging from data analysis and modeling in science to remotesensing in industrial and natural applications as well as medical imaging and nondestructive testing. Further applications come from thedata assimilation task, i.e. the use of inverse methods to control dynamical systems and provide initial states for forecasting, which is ofcentral importance in weather and climate science and an emerging technique in neuroscience and medicine.
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