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Numerical Solution of an Identifcation Problem in Electromyography

URN to cite this document: urn:nbn:de:bvb:703-epub-7068-4

Title data

Sproll, Tobias ; Schiela, Anton:
Numerical Solution of an Identifcation Problem in Electromyography.
Bayreuth , 2023 . - 21 S.

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Abstract

In medical treatment, it can be necessary to identify specific motor units in muscles from measurements on the skin. In [24], we already derived and analyzed an optimization problem suitable for such an identification. This work presents an optimization algorithm that exploits the specific mathematical structure of this problem. Our algorithm is based on a Newton line-search approach in function space with inexact function evaluations due to adaptive numerical quadrature. We present a global convergence result for this method and describe in detail its algorithmic implementation. Finally, we illustrate its practical performance by a numerical study.

Further data

Item Type:	Preprint, postprint
Keywords:	optimization in function spaces; inexact function evaluations; electromyography
Subject classification:	AMS subject classifications: 49M41, 65N30, 65N21
DDC Subjects:	500 Science > 510 Mathematics
Institutions of the University:	Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Applied Mathematics Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Applied Mathematics > Chair Applied Mathematics - Univ.-Prof. Dr. Anton Schiela Profile Fields > Advanced Fields > Nonlinear Dynamics Research Institutions > Central research institutes > Bayreuth Research Center for Modeling and Simulation - MODUS Faculties Faculties > Faculty of Mathematics, Physics und Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics Profile Fields Profile Fields > Advanced Fields Research Institutions Research Institutions > Central research institutes
Language:	German
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-7068-4
Date Deposited:	19 Jul 2023 06:40
Last Modified:	19 Jul 2023 06:42
URI:	https://epub.uni-bayreuth.de/id/eprint/7068

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