Final project for the course Numerical Linear Algebra in Autumn 2018. Submitted version.
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Updated
Jan 29, 2019 - TeX
Final project for the course Numerical Linear Algebra in Autumn 2018. Submitted version.
DCGeig is a solver for large, sparse generalized eigenvalue problems with real symmetric positive definite matrices. It computes eigenvalues and eigenvectors and can be used, e.g., for computing eigenfrequencies of finite element models.
Hierarchical solvers is an approximate sparse direct solver, written entirely in Julia.
A collection of `Pluto.jl` notebooks on Numerical Linear Algebra.
Computatinal physics University of Oslo
All my assignments to the course MM5016 at Stockholm University
Robust level-3 BLAS Inverse Iteration from the Hessenberg Matrix
An OOP Designed Multithreaded Solver for 2D Open Channel Flow in Various Programming Languages
Rational Krylov Methods for the Integration of Second Order Differential Equations and for the computation of the sinc function
Chebychev Rational approximation method for matrix exponential
Matrix function for PSBLAS
A simple particle filter simulator for robot localization in MATLAB which can show you the basics of particle filter.
This repository contains MATLAB programs and algorithms covering various numerical methods. These scripts are designed to help understand and implement fundamental numerical techniques commonly used in scientific computing.
Comparison and analysis on different algorithms to implement Pagerank, with a focus on numerical linear algebra
Algorithms for the approximation of an embedding for Markov chains.
These are some notes I wrote for internal seminars (audience made up of mathematicians, physicists and other scientists). They are only for teaching purpose.
This contains implementation of eigenvalue calculation algorithms from scratch.
MATLAB package for F(A)*b with F a Laplace transform or complete Bernstein function
Coursework, assignments, workshops for fourth year undergraduate course "Numerical Linear Algebra" at the University of Edinburgh.
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