The use of actual observations to infer the properties of a model is an inverse problem, which are often difficult as they may not have a unique solution. This book proposes a general approach that is valid for linear as well as for nonlinear problems. The philosophy is essentially probabilistic and
Inverse Problem Theory and Methods for Model Parameter Estimation || Front Matter
β Scribed by Tarantola, Albert
- Book ID
- 127050577
- Publisher
- Society for Industrial and Applied Mathematics
- Year
- 2005
- Tongue
- English
- Weight
- 113 KB
- Volume
- 10.1137/1.9780898717921
- Category
- Article
- ISBN
- 0898717922
No coin nor oath required. For personal study only.
β¦ Synopsis
While The Prediction Of Observations Is A Forward Problem, The Use Of Actual Observations To Infer The Properties Of A Model Is An Inverse Problem. Inverse Problems Are Difficult Because They May Not Have A Unique Solution. The Description Of Uncertainties Plays A Central Role In The Theory, Which Is Based On Probability Theory. This Book Proposes A General Approach That Is Valid For Linear As Well As For Nonlinear Problems. The Philosophy Is Essentially Probabilistic And Allows The Reader To Understand The Basic Difficulties Appearing In The Resolution Of Inverse Problems. The Book Attempts To Explain How A Method Of Acquisition Of Information Can Be Applied To Actual Real-world Problems, And Many Of The Arguments Are Heuristic.
π SIMILAR VOLUMES
This Publication Is Designed To Provide A Practical Understanding Of Methods Of Parameter Estimation And Uncertainty Analysis. The Practical Problems Covered Range From Simple Processing Of Time- And Space-series Data To Inversion Of Potential Field, Seismic, Electrical, And Electromagnetic Data. Th
## Abstract The leaching model PESTRAS was used to estimate sorption and degradation values for bentazone from three lysimeter datasets using the inverse modelling package PEST. Investigations were undertaken to assess the influence on calibration results of (1) values attributed to uncertain param