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Large Scale Inverse Problems

Contributor(s): Material type: TextTextDe Gruyter 2013Description: 1 online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
Other title:
  • Computational Methods and Applications in the Earth Sciences
Subject(s): Online resources: Summary: This book is thesecond volume of a three volume series recording the Radon Special Semester 2011 on Multiscale Simulation &amp Analysis in Energy and the Environment that took placein Linz, Austria, October 3-7, 2011. This volume addresses the common ground in the mathematical and computational procedures required for large-scale inverse problems and data assimilation in forefront applications. The solution of inverse problems is fundamental to a wide variety of applications such as weather forecasting, medical tomography, and oil exploration. Regularisation techniques are needed to ensure solutions of sufficient quality to be useful, and soundly theoretically based. This book addresses the common techniques required for all the applications, and is thus truly interdisciplinary. This collection of survey articles focusses on the large inverse problems commonly arising in simulation and forecasting in the earth sciences.
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This book is thesecond volume of a three volume series recording the Radon Special Semester 2011 on Multiscale Simulation &amp Analysis in Energy and the Environment that took placein Linz, Austria, October 3-7, 2011. This volume addresses the common ground in the mathematical and computational procedures required for large-scale inverse problems and data assimilation in forefront applications. The solution of inverse problems is fundamental to a wide variety of applications such as weather forecasting, medical tomography, and oil exploration. Regularisation techniques are needed to ensure solutions of sufficient quality to be useful, and soundly theoretically based. This book addresses the common techniques required for all the applications, and is thus truly interdisciplinary. This collection of survey articles focusses on the large inverse problems commonly arising in simulation and forecasting in the earth sciences.

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