Scheda programma d'esame
METODI DI APPROSSIMAZIONE
LUCA GEMIGNANI
Anno accademico2016/17
CdSMATEMATICA
Codice146AA
CFU6
PeriodoSecondo semestre
LinguaItaliano

ModuliSettoreTipoOreDocente/i
METODI DI APPROSSIMAZIONE/aMAT/08LEZIONI42
LUCA GEMIGNANI unimap
Learning outcomes
Knowledge

This course focuses on advanced techniques in numerical linear algebra (NLA) and their applications. The student who successfully completes the course will be aware of several advanced topics in numerical linear algebra and, more specifically, in structured matrix and polynomial computations. The student will be also able to have a complete look of the state of the local  research in these fields.

Assessment criteria of knowledge

Course work will  include literature research and presentation in related topics. With the  final oral presentation the student must demonstrate the ability to approach a considered research problem, and organise an effective exposition of related theoretical results and numerical solution methods.

Methods:

  • Final oral exam
  • Continuous assessment
Teaching methods

Delivery: face to face

Learning activities:

  • attending lectures
  • participation in seminar
  • preparation of oral/written report
  • participation in discussions
  • individual study

Attendance: Not mandatory

Teaching methods:

  • Lectures
  • Seminar
  • project work
Syllabus

Topics will include:

  1. Generalized eigenvalue problems, non linear eigenvalue problems, structured eigenvalue problems, parallel methods for eigenvalue computation.
  2. Fast direct and iterative linear solvers for structured and rank--structured matrices.
  3. Applications  in arge scale NLA, optimization, and large data analysis.
Bibliography

Recommended reading includes research papers published on the most relevant journals in the  field of computational mathematics and numerical/symbolic computing.

Ultimo aggiornamento 05/05/2017 13:54