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Kontak, Max: Novel algorithms of greedy-type for probability density estimation as well as linear and nonlinear inverse problems. 2018
Inhalt
Danksagung
Zusammenfassung
Abstract
Contents
Chapter 1. Introduction
Part I. Basics
Chapter 2. Notation and fundamentals of functional analysis
2.1. Spherical geometry
2.2. Fundamentals of functional analysis
2.3. Function spaces
2.4. Spherical harmonics
2.5. Zonal functions
Chapter 3. Greedy algorithms and matching pursuits
Part II. A greedy algorithm for density estimation
Chapter 4. Fundamentals of probability theory and statistics
4.1. Basics of probability theory
4.2. Kernel density estimators
4.3. Sampling from probability distributions on the real line and the sphere
Chapter 5. A greedy algorithm for the estimation ofprobability density functions
5.1. Greedy algorithms in statistics
5.2. The greedy algorithm
5.3. A synthetic example
5.4. An application: analysis and simulation of nonwoven fabrics
Part III. Greedy algorithms for inverse problems
Chapter 6. Theory of inverse problems
6.1. Linear inverse problems
6.2. Nonlinear inverse problems
Chapter 7. Inverse gravimetry
7.1. Newton’s gravitational potential
7.2. Inverse gravimetric problems
Chapter 8. Regularized Functional Matching Pursuit (RFMP)
8.1. Problem setting
8.2. Functional Matching Pursuit
8.3. Regularized Functional Matching Pursuit
8.4. Properties of the algorithm and applications
Chapter 9. Regularized Weak Functional Matching Pursuit (RWFMP)
9.1. Weak Functional Matching Pursuit (WFMP)
9.2. The Regularized Weak Functional Matching Pursuit (RWFMP)
9.3. Numerical Example
Chapter 10. RFMP for nonlinear inverse problems (RFMP_NL)
10.1. Derivation of the algorithm
10.2. Comparison to other methods
10.3. Application to the nonlinear inverse gravimetric problem
Part IV. Final remarks
Chapter 11. Conclusions and outlook
Bibliography