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OverviewThis thesis investigates the mathematical problem of parameter identification in an equation arising from the study of how cells move on an embryo during its development. The motion of the cells can be modeled as particles evolving on a two-dimensional manifold according to a stochastic differential equation. The specific focus here is on estimating the drift parameter of this equation by observing the positions of a finite number of particles at different points in time. The general approach to approximate the solution of this ill-posed problem is to minimize a Tikhonov functional based on a regularized log-likelihood. To assess the error of this approximation, tools from the theory of ill-posed problems are required. The thesis begins with a chronological review of fundamental results in nonlinear ill-posed problems, with the aim of motivating the assumptions underlying the main result as well as the techniques employed in its analysis from a historical perspective. Full Product DetailsAuthor: Nikolas UesselerPublisher: Springer Fachmedien Wiesbaden Imprint: Springer Spektrum ISBN: 9783658503437ISBN 10: 3658503432 Pages: 76 Publication Date: 30 January 2026 Audience: College/higher education , Postgraduate, Research & Scholarly Format: Paperback Publisher's Status: Forthcoming Availability: Not yet available This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of ContentsTikhonov regularization in Nonlinear Problems.- On the Conditions for Convergence Rates.- The Generalized Tikhonov Functional.- The Tools to Work with Random Data.- Application: Parameter Identification of SDEs.ReviewsAuthor InformationNikolas Uesseler is pursuing a PhD in applied mathematics at the University of Münster in the field of inverse problems and mathematical imaging in Prof. Benedikt Wirth's research group. Tab Content 6Author Website:Countries AvailableAll regions |
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