Ergebnisse für: parameter estimation
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This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The mat...
This three-part book provides a comprehensive and systematic introduction to these challenging topics such as model calibration, parameter estimation, reliability assessment, and data collection design. Part 1 covers the classical inverse problem for parameter estimation in both deterministic and st...
A practical introduction to intelligent computer vision theory, design, implementation, and technology
The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods--especially among adaboost varieties and particle ...
Classification, Parameter Estimation and State Estimation is a practical guide for data analysts and designers of measurement systems and postgraduates students that are interested in advanced measurement systems using MatLab. 'Prtools' is a powerful MatLab toolbox for pattern recognition and is wri...
This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the...
This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The mat...
This judicious selection of articles combines mathematical and numerical methods to apply parameter estimation and optimum experimental design in a range of contexts. These include fields as diverse as biology, medicine, chemistry, environmental physics, image processing and computer vision. The mat...
A practical introduction to intelligent computer vision theory, design, implementation, and technology
The past decade has witnessed epic growth in image processing and intelligent computer vision technology. Advancements in machine learning methods--especially among adaboost varieties and particle ...
This PhD thesis deals with the problem of estimating unknown parameters from noisy data using additional information. By additional information we denote any domain knowledge that is available to us except the data itself. Such prior domain knowledge very often arises naturally from the estimation p...