From 4c948e10c16718e8849d3cd6423333a876cc8971 Mon Sep 17 00:00:00 2001 From: Elgien Corey Date: Sun, 25 Aug 2024 00:22:33 +1200 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 06dd55c..7a0fcc0 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ It is a method used in solving systems of equations iteratively, rather than usi even to the largest matrices, at the cost of precision because the $x$ values are an approximation. Gauss-Seidel and Gauss-Jacobi are very similar in execution, but the feature that sets them both apart is that the former's $x$ values are modified as soon as the previous -value is evaluated (i.e. after evaluating $x_1$, the value is used as part of calculating $x_2$ and so on, leading to faster convergence. What's common for them however, +value is evaluated (i.e. after evaluating $x_1$, the value is used as part of calculating $x_2$ and so on), leading to faster convergence. What's common for them however, is that you need a (strictly) diagonally dominant matrix in order for it to work — or else you'll be stuck in an infinite loop. For a 3x3 augmented matrix, where the coefficients ($a$'s) of the 3x3 matrix are on the left side and the resultant vector $B$ (represented by $b$'s) on the right side,