Linear algebraLesson 4 of 5 in the course Determinants and linear maps

Matrix Rank: Computation, Characterizations, and Applications

5 flashcards · 5 quiz questions · 5 match pairs · 5 fill-in sentences · English

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Summary

Rank is a fundamental measure of the amount of independent information in a matrix or linear transformation. This lesson introduces rank through columns, rows, and the image of a map.

The column space of a matrix is the vector space spanned by its columns. The column rank is the dimension of that space, equivalently the largest number of linearly independent columns.

All flashcards

What is the rank of a matrix?
The dimension of its column space, row space, or associated linear map's image.
When does a matrix have rank zero?
Exactly when every entry is zero.
What is full rank for an m×nm\times n matrix?
Rank equal to the maximum possible value, min⁡(m,n)\min(m,n).
How is rank deficiency calculated?
Subtract the matrix's rank from min⁡(m,n)\min(m,n).
Why can numerical rank depend on a tolerance?
Floating-point roundoff can make small values appear zero or nonzero.

Quiz questions

  1. Which operation is an elementary row operation that preserves matrix rank?Answer: Multiply a row by a nonzero scalar.
  2. For a linear map with domain dimension nn, which equation expresses the rank–nullity theorem?Answer: rank⁡(A)+dim⁡(ker⁡f)=n\operatorname{rank}(A)+\dim(\ker f)=n
  3. If an m×nm\times n matrix has rank rr and is factored as A=CRA=CR, what are the dimensions of CC and RR?Answer: CC is m×rm\times r and RR is r×nr\times n.
  4. How can the rank of a matrix be characterized using its minors?Answer: It is the largest order of a nonzero minor.
  5. For compatible matrices AA and BB, which upper bound always holds?Answer: rank⁡(AB)≤min⁡(rank⁡(A),rank⁡(B))\operatorname{rank}(AB)\leq\min(\operatorname{rank}(A),\operatorname{rank}(B))

Based on the Wikipedia article Rank (linear algebra), licensed CC BY-SA 4.0. Adapted into a summary, flashcards and quizzes.

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