Numerical Calculus D


Students must be able to apply numerical methods for mathematical problems, such as, non linear equations, approximation of functions, integration, systems of equations and ordinary differential equations.

Students must also be able to implement computational algorithms in order to solve the aforementioned problems.

General characterization





Responsible teacher

António Manuel Morais Fernandes de Oliveira


Weekly - 3

Total - 42

Teaching language



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  • Atkinson K., An Introduction to Numerical Analysis, Wiley, Second Edition, 1989.
  • Burden R. e Faires J. , Numerical Analysis, Brooks-Cole Publishing Company, 9th Edition, 2011.
  • Conte S. e Boor C., Elementary Numerical Analysisan algorithmic approach, Mc Graw Hill, 1981.
  • Isaacson E. e Keller H., Analysis of Numerical Methods, Dover, 1994.
  • Martins, M. F. e Rebelo M., Introdução à Análise Numérica, Casa das Folhas, 1997.
  • Pina H., Métodos Numéricos, Mc Graw Hill, 1995.
  • Valença M. R., Métodos Numéricos, Livraria Minho, Terceira Edição, 1993.

Teaching method

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Evaluation method

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Subject matter

1. Errors

Absolute error,  relative error, significant digits. Condition number. Numerical algorithms stability.     

2. Polynomial approximation and interpolation

Polynomial interpolation: Lagrange and Newton formulas, cubic Spline interpolation.

Least squares approximation. 

3. Numerical integration

Newton-Cotes integration formulas,  Gaussian integration.

4. Rootfinding for nonlinear equations

Bissection method,  fixed-point iteration, Newton method, Secant method.

5. Linear systems

Vector norms and induced matrix norms.

Eigenvectors and eigenvalues. Gershgorin theorem.

Iterative methods:  general procedure, Jacobi method, Gauss-Seidel method, SOR method.

6. Numerical solution of ODE

Euler methods, Taylor methods for higher orders, Runge-Kutta methods.


Programs where the course is taught: