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Numerical Methods (MNUM)

Explanation and code for classes of numerical methods

Final Grade: 18

Subject Goals

Table of contents

Content

The language in which algorithm was developed is explicitly written in the title of each content. However, the biggest part of the code in this repository was developed in python, in order to improve understandment.

Zeros of functions - C++

Method name Explanation
Successive Bissection to add
Falsi Position to add
Picard Peano One Variable to add
Newton Method One Variable to add

Zeros of functions - Python

Method name Explanation
Sucessive Bissection to add
Falsi Position to add
Picard Peano One Variable to add
Newton Method One Variable to add
Picard Peano Two Variables to add
Newton Method Two Variable to add

Gauss - Python

Method Name Explanation
Simple Gauss Algorithm and Extern Stability
Simple Gauss with numpy to add
Gauss Seidel to add
Gauss Jacobi to add

Integrals - Python

Method Name Explanation
Regra dos Trapézios PDF
Simpson to add

Diferential Equations - Python

Method Name Explanation
Euler Image
Runge Kutta 2 Image
Runge Kutta 4 To add
Runge Kutta 4 - systems To add
Runge Kutta 4 - superior order PDF, obs: first must learn RK4 systems

Optimization - Python

Method Name Explanation
Search/Golden Search PDF
Multidimensional/Quadrica To add
Multidimensional/Gradient PDF
Multidimensional/Levenberg-Marquardt To add

Jupyter notebook

You can also check some jupyter notebook with the code:

Revisions

Here are some colected exercises for tests and exames to revision and test your knowledge.

Levenberg Marquadt

Optmization exercises

Revision to the 2nd test

These exercises do not include kaletsy algorithm.

Previous Exams

Exame Exame without solution Exam with solution Code Solution
2017.1 Link Link Link