Linear Algebra Exercises-n-Answers.pdf
Linear Algebra Exercises-n-Answers.pdf
Linear Algebra Exercises-n-Answers.pdf
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<strong>Answers</strong> to <strong>Exercises</strong> 27<br />
One.III.1.10<br />
Routine Gauss’ method gives one:<br />
⎛<br />
−3ρ 1+ρ 2<br />
−→ ⎝ 2 1 1 3<br />
⎞<br />
0 1 −2 −7<br />
−(1/2)ρ 1 +ρ 3<br />
0 9/2 1/2 7/2<br />
⎠ −(9/2)ρ2+ρ3<br />
−→<br />
and any cosmetic change, like multiplying the bottom row by 2,<br />
⎛<br />
⎝ 2 1 1 3 ⎞<br />
0 1 −2 −7⎠<br />
0 0 19 70<br />
gives another.<br />
⎛<br />
⎝ 2 1 1 3<br />
⎞<br />
0 1 −2 −7⎠<br />
0 0 19/2 35<br />
One.III.1.11 In the cases listed below, we take a, b ∈ R. Thus, some canonical forms listed below<br />
actually ( include ) ( infinitely ) ( many)<br />
cases. ( In)<br />
particular, they includes the cases a = 0 and b = 0.<br />
0 0 1 a 0 1 1 0<br />
(a) , , ,<br />
0 0 0 0 0 0 0 1<br />
( ) ( ) ( ) ( ) ( ) ( ) ( )<br />
0 0 0 1 a b 0 1 a 0 0 1 1 0 a 1 a 0 0 1 0<br />
(b)<br />
,<br />
,<br />
,<br />
,<br />
,<br />
,<br />
⎛<br />
0 0 0 0 0 0 0 0 0 0 0 0 0 1 b 0 0 1 0 0 1<br />
(c) ⎝ 0 0<br />
⎞ ⎛<br />
0 0⎠,<br />
⎝ 1 a<br />
⎞ ⎛<br />
0 0⎠,<br />
⎝ 0 1<br />
⎞ ⎛<br />
0 0⎠,<br />
⎝ 1 0<br />
⎞<br />
0 1⎠<br />
0 0 0 0 0 0 0 0<br />
⎛<br />
(d) ⎝ 0 0 0<br />
⎞ ⎛<br />
0 0 0⎠,<br />
⎝ 1 a b<br />
⎞ ⎛<br />
0 0 0⎠,<br />
⎝ 0 1 a<br />
⎞ ⎛<br />
0 0 0⎠,<br />
⎝ 0 0 1<br />
⎞ ⎛<br />
0 0 0⎠,<br />
⎝ 1 0 a<br />
⎞ ⎛<br />
0 1 b⎠,<br />
⎝ 1 a 0<br />
⎞ ⎛<br />
0 0 1⎠,<br />
⎝ 1 0 0<br />
⎞<br />
0 1 0⎠<br />
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1<br />
One.III.1.12 A nonsingular homogeneous linear system has a unique solution. So a nonsingular matrix<br />
must reduce to a (square) matrix that is all 0’s except for 1’s down the upper-left to lower-right diagonal,<br />
e.g.,<br />
⎛<br />
( )<br />
1 0<br />
, or ⎝ 1 0 0 ⎞<br />
0 1 0⎠ , etc.<br />
0 1<br />
0 0 1<br />
One.III.1.13 (a) The ρ i ↔ ρ i operation does not change A.<br />
(b) For instance, ( ) ( ) ( )<br />
1 2 −ρ 1+ρ 1 0 0 ρ 1+ρ 1 0 0<br />
−→ −→<br />
3 4 3 4 3 4<br />
leaves the matrix changed.<br />
(c) If i ≠ j then<br />
⎛<br />
⎞<br />
.<br />
.<br />
a i,1 · · · a i,n<br />
.<br />
⎜<br />
⎝a j,1 · · · a j,n<br />
⎟<br />
⎠<br />
.<br />
kρ i +ρ j<br />
−→<br />
−kρ i +ρ j<br />
−→<br />
⎛<br />
⎞<br />
.<br />
.<br />
a i,1 · · · a i,n<br />
.<br />
⎜<br />
⎝ka i,1 + a j,1 · · · ka i,n + a j,n<br />
⎟<br />
⎠<br />
.<br />
⎛<br />
.<br />
.<br />
a i,1 · · · a i,n<br />
.<br />
⎜<br />
⎝−ka i,1 + ka i,1 + a j,1 · · · −ka i,n + ka i,n + a j,n<br />
⎟<br />
⎠<br />
.<br />
does indeed give A back. (Of course, if i = j then the third matrix would have entries of the form<br />
−k(ka i,j + a i,j ) + ka i,j + a i,j .)<br />
⎞<br />
Subsection One.III.2: Row Equivalence<br />
One.III.2.11<br />
Bring each to reduced echelon form and compare.