Numerical analysis in julija
In this organization , you can find the code for problems I solved for the Numerical Mathematics course. The code is written in Julia.
Pinned Repositories
.github
In this organization , you can find the code for problems I solved for the Numerical Mathematics course. The code is written in Julia.
Interpolation_with_the_barycentric_formula.jl
Implementation of polynomial interpolation using the Barycentric Lagrange formula with Chebyshev points. The program computes polynomial interpolants for three different functions on specified intervals, and determines the polynomial degree necessary to ensure that the error does not exceed 1e-6
Mathematical_pendulum_using_the_Runge_Kutta_method.jl
Implementation of simulation of a mathematical pendulum's motion using the Runge-Kutta fourth-order method. Compares the pendulum's behavior with that of a harmonic oscillator and visualizes how its oscillation period varies with energy.
Methode_of_conjugate_gradients.lj
Implementation of Conjugate Gradient method to solve a linear system Ax = b for sparse matrices represented by a custom data type (ScatteredArray).
Numerical analysis in julija's Repositories
Numerical-analysis-in-julija/.github
In this organization , you can find the code for problems I solved for the Numerical Mathematics course. The code is written in Julia.
Numerical-analysis-in-julija/Interpolation_with_the_barycentric_formula.jl
Implementation of polynomial interpolation using the Barycentric Lagrange formula with Chebyshev points. The program computes polynomial interpolants for three different functions on specified intervals, and determines the polynomial degree necessary to ensure that the error does not exceed 1e-6
Numerical-analysis-in-julija/Mathematical_pendulum_using_the_Runge_Kutta_method.jl
Implementation of simulation of a mathematical pendulum's motion using the Runge-Kutta fourth-order method. Compares the pendulum's behavior with that of a harmonic oscillator and visualizes how its oscillation period varies with energy.
Numerical-analysis-in-julija/Methode_of_conjugate_gradients.lj
Implementation of Conjugate Gradient method to solve a linear system Ax = b for sparse matrices represented by a custom data type (ScatteredArray).