Numerical Analysis II
No Thumbnail Available
Date
2026
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
University Hassiba Benbouali of Chlef
Abstract
Numerical analysis forms the cornerstone of modern scientific computing, enabling the
solution of complex mathematical problems where analytical methods fail. This discipline is crucial for physics simulations, engineering design, financial modeling, and artificial intelligence applications. Our course material equips second-year LMD mathematics
students with fundamental computational techniques, beginning with linear system solutions (Gaussian elimination, iterative methods) in Chapter 1. Chapter 2 covers eigenvalue
problems, essential for stability analysis and machine learning algorithms. First-order differential equations (Chapter 3) model dynamic systems in biology and economics, solved
numerically via Euler and Runge-Kutta methods. The final chapter tackles nonlinear
algebraic systems using Newton-Raphson iterations, vital for optimization and control
theory.
Through algorithmic rigor and MATLAB examples, we emphasize error analysis and
computational efficiency. Progressive exercises develop both theoretical understanding
and practical implementation skills, preparing students for research and industry challenges in applied mathematics.
Description
Intended for students of Second Year LMD Mathematics Degree (L2)
Faculty of Exact Sciences And Informatics
Department of Mathematics