Study-unit NUMERICAL MODELS
| Course name | Mathematics |
|---|---|
| Study-unit Code | 55A00097 |
| Curriculum | Matematica per l'economia e la finanza |
| Lecturer | Bruno Iannazzo |
| Lecturers |
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| Hours |
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| CFU | 6 |
| Course Regulation | Coorte 2023 |
| Supplied | 2023/24 |
| Supplied other course regulation | |
| Learning activities | Affine/integrativa |
| Area | Attività formative affini o integrative |
| Sector | MAT/08 |
| Type of study-unit | Opzionale (Optional) |
| Type of learning activities | Attività formativa monodisciplinare |
| Language of instruction | Italian or English (only if all students agree). |
| Contents | Selected topics in Numerical Linear Algebra for Numerical Modeling |
| Reference texts | Horn, Johnson, Matrix Analysis. Horn, Johnson, Topics in Matrix Analysis. Material provided by the teacher. During the course text based on the topics chosen by the students will be indicated. |
| Educational objectives | The course aims at presenting advanced topics of numerical analysis and applications to mathematical modeling. The mathematical models will be studied in detail. The student will be aware of advanced methodologies in numerical analysis, and will use some scientific research techniques. The student will be able to appreciate the richness of mathematical modeling with the application of linear algebra techniques to problems in very different contexts (imaging, applied probability, social network analysis). |
| Prerequisites | Linear algebra, Multivariate analysis, Numerical Analysis (it may be useful an elementary knowledge of Functional Analysis and Differential Geometry). |
| Teaching methods | Face-to-face lectures and laboratory with Matlab/Octave. |
| Learning verification modality | Oral exam of about one hour. (Optional mid-term exam on a presentation.) |
| Extended program | Matrix analysis. Positivity: Perron and Frobenius theory. Numerical methods for Markov chains. Numerical Range. Localization of eigenvalues. Krylov subspace method. Tensor analysis. There will be applications to mathematical models. |
| Obiettivi Agenda 2030 per lo sviluppo sostenibile |