An eigenvector is a non-zero vector whose direction is unchanged by a linear transformation, except for scaling.
What Is Eigenvector?
An eigenvector is a non-zero vector whose direction is unchanged by a linear transformation, except for scaling.
Examples of Eigenvector
1
If Av=3v, then v is an eigenvector with eigenvalue 3.Formula and Key Points
Formula / rule
Av=λv
- Know the definition and standard notation for Eigenvector.
- Be able to recognise or compute eigenvector in a small example.
- Connect the concept to nearby topics in the same subject before using it in larger CSE problems.
Why This Matters in Computer Science
Used in computer graphics, machine learning, computer vision, signal processing, robotics and scientific computing. Used in PCA, PageRank, computer vision and spectral clustering.
Related Math Terms
Eigenvector: Frequently Asked Questions
What is Eigenvector?
An eigenvector is a non-zero vector whose direction is unchanged by a linear transformation, except for scaling.
Why is Eigenvector useful in computer science?
Used in computer graphics, machine learning, computer vision, signal processing, robotics and scientific computing. Used in PCA, PageRank, computer vision and spectral clustering.