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Les deux révisions précédentes Révision précédente Prochaine révision | Révision précédente | ||
teaching:methcalchim:system_of_linear_equations [2018/10/08 13:27] – villersd | teaching:methcalchim:system_of_linear_equations [2018/10/18 10:10] (Version actuelle) – villersd | ||
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* 2.2 Gaussian Elimination with Backsubstitution | * 2.2 Gaussian Elimination with Backsubstitution | ||
* 2.3 LU Decomposition and Its Application | * 2.3 LU Decomposition and Its Application | ||
+ | * Python [[https:// | ||
+ | * [[https:// | ||
* Time complexity analysis | * Time complexity analysis | ||
* Hint : in Python, use the timeit module | * Hint : in Python, use the timeit module | ||
+ | |||
+ | ===== Jupyter notebooks ===== | ||
+ | * Example file (to be continued) : [[https:// | ||
===== Exercices and applications ===== | ===== Exercices and applications ===== | ||
Ligne 27: | Ligne 32: | ||
* Using [[wp> | * Using [[wp> | ||
* ? Python library with Thomas algorithm | * ? Python library with Thomas algorithm | ||
+ | |||
+ | ===== What you must have learned in this chapter ===== | ||
+ | * Except ill-conditionned, | ||
+ | * The accuracy is determined by the number of numerical figures which are encoded in floating point description | ||
+ | * For a general system of n equations, diagonalisation requires of the order of n< | ||
+ | * If the coefficient matrix is the same for different systems (only the independent coefficients are different), it is possible to solve systems with the order of n< | ||
===== References : ===== | ===== References : ===== |