Numerical computation in native Haskell

SCIRun is a Problem Solving Environment, for modeling, simulation and visualization of scientific problems. This is version 5, the upgraded version of SCIRun v4.

A Julia Basket of Hand-Picked Krylov Methods

Structured Matrix Package (LBNL)

Matlab implementation to simulate the non-linear dynamics of a fixed-wing unmanned areal glider. Includes tools to calculate aerodynamic coefficients using a vortex lattice method implementation, and to extract longitudinal and lateral linear systems around the trimmed gliding state.

A free LDL factorisation routine

A linear algebra library for JavaScript 🔢

Measure the distance between two spectra/signals using optimal transport and related metrics

Nengo library of additional extensions

Math for Machine Learning and Deep Learning

Julia package for representing linear, time-invariant system models and operations defined on them.

Solve matrix equations in python.

Numerical methods implementation in Python 3.

Láminas y códigos para el curso INFO183: Análisis de sistemas lineales de la Universidad Austral de Chile

pentapy: A Python toolbox for pentadiagonal linear systems

Numerical methods implementation in MATLAB.

Controlled Invariant Sets in Two Moves

This is the source code for my paper titled, "A New Fast Algorithm to Estimate Real-Time Phasors Using Adaptive Signal Processing", published in IEEE Trans. Power Delivery journal, Link :

Implementation of Jacobi method, Conjugate Gradient method using CUDA API.

MATLAB Live demonstrations of Signals and Systems concepts. Originally created for in-class demonstration. Feel free to use them in your teaching and/or study.

Implementation of numerical analysis algorithms in python & M (octave/matlab).

Public repository of the spaND algorithm (~mirror of the private repo)

Gaussian belief propagation solver for noisy linear systems with real coefficients and variables.

Notes for a Linear Systems Class

Implementation for different numerical algorithms

In this paper, we will be evaluating numerical methods for direct and iterative solvers of linear systems. From class we have discussed the various methods; Gauss elimination with pivoting techniques, Jacobi Iterative Method, Gauss-Seidel Iterative Method, Successive Over-Relaxation Method, Iterative Refinement Method, and Conjugate Gradient Method. In this paper, using Python programming language, we will discuss how each method evaluates various linear systems of equations, and then we will discuss the complexity, accuracy, and stability of each method

Project for Unicamp course EA619 in signals and linear systems. Convolution of different impulse response signals as means of applying reverberation to the sound of another signal.

Numerical precision analysis of different operations. Image handling and prosessing of images