MATH 323 Lecture 5

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Elementary Matrices

System of equations now in form Ax=b, where A is m×n, and x and b are n

For a non-singular, invertible m×m matrix M, MAx=Mb, and this system will be equivalent to the original. M could even be product of several matrices: M=EkEk1E2E1, where Ei is an elementary matrix.

Types of elementary matrices (each corresponds to rules of matrix):

  1. E obtained by interchanging two rows of identity matrix I
    • EA permutes rows
    • AE permutes columns
  2. E obtained by multiplying row of identity matrix I by a nonzero constant α
    • EA scales corresponding row by α
    • AE scales corresponding column by α.
  3. E obtained from I by adding a multiple of one row i to another row i:
    • EA adds multiple of row i to row i
    • AE adds multiple of column i to column i
Note: I (and thus E) is always a square matrix, but A can be of any size

E is a n×n matrix: we can think of it as being obtained from I by either a row operation or column operation. If A is a n×r matrix, premultiplying A by E has the effect of performing the same row operation on A. If B is a m×n matrix, postmultiplying B by E is equivalent to performing that same column operation on B.

Theorem 1.4.1

If E is an elementary matrix, then E is nonsingular and E1 is an elementary matrix of the same type as E

  1. EE=I, since interchanging two rows twice undoes the effect, so E=E1
  2. if E has an α at position i,i. E1 will have 1/α at i,i
  3. E has a m at position i,j, where ij. E1 will have m at i,j. In multiplying E by E1, position i,j will be product of ith row and jth column: k=1nei,kek,j1=mm=0


Row Equivalence

B is row equivalent to A (written BAAB iff there exists a finite sequence E1,E2,,Ek of elementary matrices such that B=EkEk1E2E1A. In other words, B can be obtained from A by a finite number of row operations.

By extension, two augmented matrices (A|b) and (B|c) are row equivalent iff Ax=b and Bx=c are equivalent systems.

Theorem 1.4.2

Equivlent Conditions for Nonsingularity

Let A be a n×n matrix. Then the following are equivalent:

  1. A is nonsingular
  2. Ax=0 has only trivial solution 0
  3. A is row equivalent to identity matrix of size n (AIn)

(1) → (2): Let x^ be solution of Ax=0. So Ax^=0 can become A1Ax^=A10. Ix^=0, so x^=0

(2) → (3): Rewrite Ax=0 in row echelon form as Ux=0. If one diagonal entry of U is 0, then there is at least one free variable and infinitely many solutions, one of which is nonzero. This leads to a contradiction, so all diagonal entries of U must be 1, so rref will be identity matrix.

(3) → (1): If A is row equivalent to I, then there exists a sequence of elementary matrices E1,,Ek such that i=k1Ei=A. Therefore, A1=k=1kEi1 (note reverse order), so A is nonsingular.


Corrolary 1.4.3

The n×n system of equations Ax=b has a unique solution iff A is nonsingular.


  • A is nonsingular, Ax=b can be rewritten as x^=A1b
  • Assume unique solution x^ exists. If A were singular then homogeneous system Ax=0 would have a nonzero solution y0 (by Theorem 1.4.2). If this were the case, ... there would be another solution, which is a contradiction.