Introduction to probability (Course & exercises)
| dc.contributor.author | ATIL, Lynda | |
| dc.date.accessioned | 2025-12-16T13:49:37Z | |
| dc.date.available | 2025-12-16T13:49:37Z | |
| dc.date.issued | 2025-12-16 | |
| dc.description.abstract | This handout is intended for second-year Mathematics students, as part of the Numerical Analysis 2 module. This document is structured into four chapters: 1. Reminders and supplements on matrices: This chapter aims to recall and demonstrate a number of results related to matrices and vector spaces. 2.of finite dimension, and which will be constantly used throughout the rest of the handout. Numerical resolution of linear equation systems: We study direct methods (Gauss, Cholesky) that allow us to obtain the solution in a finite number of operations and iterative methods (Jacobi, Gauss-Seidel) that seek the solution step by step starting from an arbitrary initial vector to solve a linear system. 3. Calculation of eigenvalues and eigenvectors: This chapter covers methods for calculating approximations of the set of eigenvalues of a matrix A and the associated eigenvectors. 4. Associated eigenvectors. Numerical resolution of differential equations: "We address different numerical methods for the approximate solutions of ordinary differential equations." | |
| dc.identifier.uri | https://dspace.ummto.dz/handle/ummto/29453 | |
| dc.language.iso | en | |
| dc.publisher | ummto.faculté des sciences | |
| dc.subject | vector spaces | |
| dc.subject | linear equations | |
| dc.subject | Gauss methods | |
| dc.subject | Cholesky methods | |
| dc.subject | Jacobi methods | |
| dc.subject | Gauss-Seidel method | |
| dc.subject | numerical analysis | |
| dc.title | Introduction to probability (Course & exercises) | |
| dc.type | Other |