Applications of Row Reduction - Gaussian Elimination I - Wild Linear Algebra A - NJ Wildberger

Applications of Row Reduction - Gaussian Elimination I - Wild Linear Algebra A - NJ Wildberger

Insights into Mathematics via YouTube Direct link

Finding eigenvalues and eigenvectors

17 of 22

17 of 22

Finding eigenvalues and eigenvectors

Class Central Classrooms beta

YouTube videos curated by Class Central.

Classroom Contents

Applications of Row Reduction - Gaussian Elimination I - Wild Linear Algebra A - NJ Wildberger

Automatically move to the next video in the Classroom when playback concludes

  1. 1 CONTENT SUMMARY: pg 1: @ 3 main problems of Linear Algebra;
  2. 2 pg 2: @ Inverting a linear change of coordinates; example;
  3. 3 pg 3: @ example finished; new idea: introduce a y-sub-i matrix; to obtain the inverse of a matrix;
  4. 4 pg 4: @ Theorem concerning an invertible matrix;
  5. 5 pg 5: @ Finding eigenvalues and eigenvectors of an nXn matrix; remark about the Homogeneous case;
  6. 6 g 6: @14:23 The eigenvalue problem using row reduction; example1; check of result @;
  7. 7 pg 7: @ example2 as a reminder of the physical meaning of an eigenvector equation see WildLinAlg7;
  8. 8 pg 8: @ example2 continued; finding the eigenvectors using row reduction; perpendicular eigenvectors;
  9. 9 pg 9: @27:52 How to calculate a determinant; characteristics of a determinant; as the volume of a parallelpiped; properties of a determinant necessary to do row reduction @;
  10. 10 pg 10: @ the determinant of an upper triangular matrix;
  11. 11 pg 11: @35:11 example: putting a matrix in upper triangular form to obtain its determinant; remark about this lesson @ ;
  12. 12 pg 12: @ exercises 15.1:2 ; invert some systems using row reduction; find inverse matrices;
  13. 13 pg 13: @ exercises 15.3:4 ; find eigenvalues and eigenvectors; compute determinants; THANKS to EmptySpaceEnterprise
  14. 14 Introduction
  15. 15 Inverting a linear change of co - ods
  16. 16 Inverting a square invertible matrix by row reduction
  17. 17 Finding eigenvalues and eigenvectors
  18. 18 The eigenvalue problem using row reduction
  19. 19 How to calculate a determinant
  20. 20 If A is upper triangular then detA= product of diagonal entries
  21. 21 Exercises: invert some systems using row reduction; find inverse matrices
  22. 22 exercises 15.3:4 ; find eigenvalues and eigenvectors; compute determinants

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.