{"id":5846,"date":"2023-10-04T17:45:36","date_gmt":"2023-10-04T14:45:36","guid":{"rendered":"https:\/\/iamm.in.ua\/?p=5846"},"modified":"2023-11-01T13:11:29","modified_gmt":"2023-11-01T10:11:29","slug":"5846","status":"publish","type":"post","link":"https:\/\/iamm.in.ua\/?p=5846&lang=en","title":{"rendered":"SEMINAR \u201cContemporary Analysis and Partial Differential Equations\u201d (20.10.2023)"},"content":{"rendered":"

\"\"<\/p>\n

\"\"<\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n

 <\/p>\n

Sergei Solodky<\/span><\/strong><\/p>\n

Institute of Mathematics of NASU, Ukraine,<\/span>
\nUniversity of Giessen, Germany<\/span><\/p>\n

solodky@imath.kiev.ua<\/span><\/p>\n

Optimization of Numerical Differentiation Methods. <\/span>
\nApproximation and Information Aspects <\/span>
\n<\/em><\/strong><\/p>\n

Friday, 20 October 2023 at 12:00<\/span><\/p>\n

On line: https:\/\/meet.google.com\/afw-vnwo-dfb<\/a><\/span><\/p>\n

Abstract<\/strong><\/span><\/p>\n

In the talk, I will incorporate the so-called self-regularization into the numerical differentiation of multivariable functions. The proposed approach is a combination of the truncation method and a discretization scheme using the idea of a hyperbolic cross. It will be shown that numerical differentiation methods constructed in this way not only have a simple implementation but are also optimal in terms of the accuracy and volume of discrete information used.<\/span><\/p>\n

Seminar video report<\/span><\/p>\n