/num-analysis

Learning some Numerical Analysis

Primary LanguageGo

Overview

I am learning some Numerical Analysis from video lectures posted on Justin Solomon's YouTube channel. I will try implementing some of the stuff I learn, and I will put it here.

Contents

  • kahan - a simple algorithm for summing up numbers without error.
  • linalg/ludecomp - decompose a matrix A into PAQ=LU, then use the factorized form to solve Ax=b.
  • linalg/cholesky - decompose symmetric positive-definite matrices using Cholesky factorization.
  • linalg/qrdecomp - decompose any matrix A into QR using various methods.
  • linalg/leastsquares - use QR decomposition for more stable least-squares approximations.
  • linalg/eigen - approximate the eigenpairs of some matrices.
  • linalg/svd - compute Singular Value Decompositions of matrices.
  • realroots - approximate the roots of arbitrary single-variable functions.
  • mvroots - approximate the roots of multi-variable functions and complex polynomials.
  • unitcircles - a simple HTML app to visualize different p-norms.
  • regression - basic regression using least squares.
  • imagealign - align a crooked image to a reference image using least squares.
  • newton-basins - visualize the "Newton Basins" of polynomials.
  • conjgrad - basic Conjugate Gradient implementation.
  • blurify - blur or sharpen an image.
  • interp - various interpolation algorithms.
  • interp/visualizer - visualize interpolations.
  • integration - numerical integration using polynomial approximations.
  • autodiff - a basic automatic differentiation system.