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 remote
sensing in industrial and natural applications as well as medical imaging and non-destructive testing. Further applications come from the
data assimilation task, i.e. the use of inverse methods to control dynamical systems and provide initial states for forecasting, which is of
central importance in weather and climate science and an emerging technique in neuroscience and medicine.