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Linear Algebra Exercises-n-Answers.pdf

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28 <strong>Linear</strong> <strong>Algebra</strong>, by Hefferon<br />

(a) The first gives<br />

while the second gives<br />

( )<br />

−4ρ 1 +ρ 2 1 2<br />

−→<br />

0 0<br />

( ) ( )<br />

ρ 1 ↔ρ 2 1 2 −2ρ 2 +ρ 1 1 0<br />

−→ −→<br />

0 1<br />

0 1<br />

The two reduced echelon form matrices are not identical, and so the original matrices are not row<br />

equivalent.<br />

(b) The first is this.<br />

⎛<br />

−3ρ 1 +ρ 2<br />

−→ ⎝ 1 0 2 ⎞ ⎛<br />

0 −1 −5⎠ −ρ 2+ρ 3<br />

−→ ⎝ 1 0 2 ⎞ ⎛<br />

0 −1 −5⎠ −ρ 2<br />

−→ ⎝ 1 0 2 ⎞<br />

0 1 5⎠<br />

−5ρ 1+ρ 3<br />

0 −1 −5<br />

0 0 0 0 0 0<br />

The second is this.<br />

−2ρ 1 +ρ 3<br />

−→<br />

⎛<br />

⎝ 1 0 2 ⎞<br />

0 2 10<br />

0 0 0<br />

⎠ (1/2)ρ 2<br />

−→<br />

⎛<br />

⎝ 1 0 2 ⎞<br />

0 1 5⎠<br />

0 0 0<br />

These two are row equivalent.<br />

(c) These two are not row equivalent because they have different sizes.<br />

(d) The first,<br />

( ) ( ) ( )<br />

ρ 1 +ρ 2 1 1 1 (1/3)ρ 2 1 1 1 −ρ 2 +ρ 1 1 0 0<br />

−→ −→ −→<br />

0 3 3 0 1 1 0 1 1<br />

and the second.<br />

These are not row equivalent.<br />

(e) Here the first is<br />

while this is the second.<br />

These are not row equivalent.<br />

( ) ( ) ( )<br />

ρ 1↔ρ 2 2 2 5 (1/2)ρ 1 1 1 5/2 −ρ 2+ρ 1 1 0 17/6<br />

−→ −→<br />

−→<br />

0 3 −1 (1/3)ρ 2<br />

0 1 −1/3 0 1 −1/3<br />

( ) ( )<br />

(1/3)ρ 2 1 1 1 −ρ 2 +ρ 1 1 1 0<br />

−→ −→<br />

0 0 1 0 0 1<br />

( ) ( )<br />

ρ 1 ↔ρ 2 1 −1 1 ρ 2 +ρ 1 1 0 3<br />

−→ −→<br />

0 1 2 0 1 2<br />

One.III.2.12 First, the only matrix row equivalent to the matrix of all 0’s is itself (since row operations<br />

have no effect).<br />

Second, the matrices that reduce to (<br />

1<br />

)<br />

a<br />

0 0<br />

have the form (<br />

b<br />

)<br />

ba<br />

c ca<br />

(where a, b, c ∈ R).<br />

Next, the matrices that reduce to (<br />

0<br />

)<br />

1<br />

0 0<br />

have the form (<br />

0<br />

)<br />

a<br />

0 b<br />

(where a, b ∈ R).<br />

Finally, the matrices that reduce to (<br />

1<br />

)<br />

0<br />

0 1<br />

are the nonsingular matrices. That’s because a linear system for which this is the matrix of coefficients<br />

will have a unique solution, and that is the definition of nonsingular. (Another way to say the same<br />

thing is to say that they fall into none of the above classes.)

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