https://github.com/perpendicooler/applied-linear-algebra-modified-new-functions

Applied Linear Algebra
https://github.com/perpendicooler/applied-linear-algebra-modified-new-functions

1138-bus-matrix cholesky-decomposition cholesky-factorization conjugate matrix preconditioning sparse-matrix tensor tridiagonal-matrix-algorithm ttm ttt ttv

Last synced: 2 months ago
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Applied Linear Algebra

• Host: GitHub
• URL: https://github.com/perpendicooler/applied-linear-algebra-modified-new-functions
• Owner: perpendicooler
• Created: 2024-01-20T08:45:16.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-02-24T21:50:48.000Z (about 1 year ago)
• Last Synced: 2025-01-23T14:30:42.373Z (4 months ago)
• Topics: 1138-bus-matrix, cholesky-decomposition, cholesky-factorization, conjugate, matrix, preconditioning, sparse-matrix, tensor, tridiagonal-matrix-algorithm, ttm, ttt, ttv
• Language: MATLAB
• Homepage:
• Size: 3.25 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: Readme.txt

Awesome Lists containing this project

README

        
1. For Problem one cholesky analysis

   

  - Just Run and modify matrices as your wish

2. Solve Tridiagonal System

   

  - It will solve the unknown of the tridiagonal

  - just input the value of the funciton and call from command window

3. Tensor

  - ttm, ttv, ttt those are for matrices vectors and tensors. 

  - Command a good example and be careful about definig tensor vector and matrices

4. For pcg

  

  - Make sure you have all the files. Generate poisson, exact solution poisson, 1138.mat file and turn them as suitesparse matrices

  - Run the test file it will call automatically other functions as well

  - Then for plotting Run the plot_results file

  - Lastly, For table just run the Tables.m files...