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==Math 163b==
==Linear Algebra Extra Credit==

For MATH 511, Submitted 11/9/2010

'''With examples, explain...'''


===#1===
===#1===


Find <math>I = \int_1^2 x\ln{x}\, \mathrm dx\!</math>.
'''...how to find matrix inverses using row operations.'''


Let <math>u = \ln{x}</math> and <math>dv = x\,\mathrm dx\!</math>.
We augment ''A'' with ''I'', then do row operations until we have ''I''|''A<sup>-1</sup>''.


Then, <math>du = \frac{1}{x}\, \mathrm dx\!</math> and <math>v = \frac{x^2}{2}</math>.
<math>
A =
\left[\begin{array}{ccc}
0 & 2 & 4 \\
2 & 4 & 2 \\
3 & 3 & 1
\end{array}\right]
</math>


So,
<math>
(A|I) =
\left[\begin{array}{ccc|ccc}
0 & 2 & 4 & 1 & 0 & 0 \\
2 & 4 & 2 & 0 & 1 & 0 \\
3 & 3 & 1 & 0 & 0 & 1
\end{array}\right]</math>


<math>I=uv\right|_1^2-\int_1^2 v\,\mathrm du.\!</math>
<math>\rightarrow

\left[\begin{array}{ccc|ccc}
2 & 4 & 2 & 0 & 1 & 0 \\
0 & 2 & 4 & 1 & 0 & 0 \\
3 & 3 & 1 & 0 & 0 & 1
\end{array}\right]
</math>

<math>\rightarrow

\left[\begin{array}{ccc|ccc}
1 & 2 & 1 & 0 & 1/2 & 0 \\
0 & 2 & 4 & 1 & 0 & 0 \\
3 & 3 & 1 & 0 & 0 & 1
\end{array}\right]
</math>

<math>\rightarrow

\left[\begin{array}{ccc|ccc}
1 & 2 & 1 & 0 & 1/2 & 0 \\
0 & 2 & 4 & 1 & 0 & 0 \\
0 & -3 & -2 & 0 & -3/2 & 1
\end{array}\right]
</math>

<math>\rightarrow

\left[\begin{array}{ccc|ccc}
1 & 0 & -3 & -1 & 1/2 & 0 \\
0 & 1 & 2 & 1/2 & 0 & 0 \\
0 & 0 & 4 & 3/2 & -3/2 & 1
\end{array}\right]
</math>

<math>\rightarrow

\left[\begin{array}{ccc|ccc}
1 & 0 & -3 & -1 & 1/2 & 0 \\
0 & 1 & 2 & 1/2 & 0 & 0 \\
0 & 0 & 1 & 3/8 & -3/8 & 1/4
\end{array}\right]
</math>


<math>\rightarrow

\left[\begin{array}{ccc|ccc}
1 & 0 & 0 & 1/8 & -5/8 & 3/4 \\
0 & 1 & 0 & -1/4 & 3/4 & -1/2 \\
0 & 0 & 1 & 3/8 & -3/8 & 1/4
\end{array}\right]
</math>

<math>
A^{-1} =
\left[\begin{array}{ccc}
1/8 & -5/8 & 3/4 \\
-1/4 & 3/4 & -1/2 \\
3/8 & -3/8 & 1/4
\end{array}\right]
</math>


===#2===
===#2===
'''...how to recognize when a square matrix is not invertible using the method from #1.'''<br><br>
<math>
A =
\left[\begin{array}{ccc}
1 & 2 & 1 \\
2 & 1 & -1 \\
1 & 5 & 4
\end{array}\right]
</math>

<math>
(A|I) =
\left[\begin{array}{ccc|ccc}
1 & 2 & 1 & 1 & 0 & 0 \\
2 & 1 & -1 & 0 & 1 & 0 \\
1 & 5 & 4 & 0 & 0 & 1
\end{array}\right]</math>

<math>\rightarrow

\left[\begin{array}{ccc|ccc}
1 & 2 & 1 & 1 & 0 & 0 \\
0 & -3 & -3 & -2 & 1 & 0 \\
1 & 3 & 3 & -1 & 0 & 1
\end{array}\right]
</math>

<math>\rightarrow

\left[\begin{array}{ccc|ccc}
1 & 2 & 1 & 0 & 1/2 & 0 \\
0 & -3 & -3 & 1 & 0 & 0 \\
0 & 0 & 0 & -3 & 1 & 1
\end{array}\right]
</math>

Since the A side of the augmentation now has a zero row, A is not invertible.

===#3===
'''...how to express an invertible matrix as a product of elementary matrices using the method from #1.'''

# List the row ops used
# Replace each with its “undo” row operation
# Convert these to elementary matrices (apply to I) and list left to right

<math>
A =
\left[\begin{array}{ccc}
0 & 2 & 4 \\
2 & 4 & 2 \\
3 & 3 & 1
\end{array}\right]
</math>

'''Step 1'''
<math>R1 \leftrightarrow R2</math><br><br>
<math>1/2 R1 \rightarrow R1</math><br><br>
<math>R3 - 3R1 \rightarrow R3</math><br><br>
<math>1/2 R2 \rightarrow R2</math><br><br>
<math>R1 - 2R2 \rightarrow R1</math><br><br>
<math>R3 + 3R2 \rightarrow R3</math><br><br>
<math>1/4 R3 \rightarrow R3</math><br><br>
<math>R2 - 2R3 \rightarrow R2</math><br><br>
<math>R1 + 3R3 \rightarrow R1</math><br><br>


'''Step 2'''
<math>R1 \leftrightarrow R2</math><br><br>
<math>2R1 \rightarrow R1</math><br><br>
<math>R3 + 3R1 \rightarrow R3</math><br><br>
<math>2R2 \rightarrow R2</math><br><br>
<math>R1 + 2R2 \rightarrow R1</math><br><br>
<math>R3 - 3R2 \rightarrow R3</math><br><br>
<math>4R3 \rightarrow R3</math><br><br>
<math>R2 + 2R3 \rightarrow R2</math><br><br>
<math>R1 - 3R3 \rightarrow R1</math><br><br>

'''Step 3'''
<math>
\left[\begin{array}{ccc}
0 & 1 & 0 \\
1 & 0 & 0 \\
0 & 0 & 1
\end{array}\right]\ast\left[\begin{array}{ccc}
2 & 0 & 0 \\
0 & 1 & 0 \\
0 & 0 & 1
\end{array}\right]\ast\left[\begin{array}{ccc}
1 & 0 & 0 \\
0 & 1 & 0 \\
3 & 0 & 1
\end{array}\right]\ast\left[\begin{array}{ccc}
1 & 0 & 0 \\
0 & 2 & 0 \\
0 & 0 & 1
\end{array}\right]<br>\ast\left[\begin{array}{ccc}
1 & 2 & 0 \\
0 & 1 & 0 \\
0 & 0 & 1 \end{array}\right]\ast\left[\begin{array}{ccc}
1 & 0 & 0 \\
0 & 1 & 0 \\
0 & -3 & 1
\end{array}\right]\ast\left[\begin{array}{ccc}
1 & 0 & 0 \\
0 & 1 & 0 \\
0 & 0 & 4
\end{array}\right]\ast\left[\begin{array}{ccc}
1 & 0 & 0 \\
0 & 1 & 2 \\
0 & 0 & 1
\end{array}\right]<br>\ast\left[\begin{array}{ccc}
1 & 0 & -3 \\
0 & 1 & 0 \\
0 & 0 & 1
\end{array}\right] =
\left[\begin{array}{ccc}
1/8 & -5/8 & 3/4 \\
-1/4 & 3/4 & -1/2 \\
3/8 & -3/8 & 1/4
\end{array}\right] = A^{-1}
</math>

===#4===
'''...how to calculate the determinant of a square matrix A.'''

First we must know that if we have a 2x2 matrix

<math>
A =
\left[\begin{array}{cc}
a & b \\
c & d
\end{array}\right],
</math>

then det(''A'') is the scalar ''ad'' - ''bc''.

We must also know that ''Ã''<sub>''ij''</sub> is the matrix obtained by deleting row ''i'' and column ''j'' from ''A''.

Now, the cofactor of the entry of ''A'' in row ''i'', column ''j'' is the scalar (-1)<sup>''i+j''</sup>det(Ã<sub>''ij''</sub>).

The determinant of A equals the sum of the products of each entry in row 1 of A multiplied by its cofactor.

So if we have
<math>
A =
\left[\begin{array}{cccc}
2 & 0 & 0 & 1\\
0 & 1 & 3 & -3 \\
-2 & -3 & -5 & 2 \\
4 & -4 & 4 & -6
\end{array}\right],</math>

<math>|A| = (-1)^2(2)|\tilde{A}_{11}|+(-1)^3(0)|\tilde{A}_{12}|+(-1)^4(0)|\tilde{A}_{13}|+(-1)^5(1)|\tilde{A}_{14}|.</math>

Therefore,


<math>|A| = (-1)^2(2)\left|\begin{array}{cccc}
Find <math>I = \int (x+\ln{x}+e^x)\,\mathrm dx\!</math>.
1 & 3 & -3 \\
-3 & -5 & 2 \\
-4 & 4 & -6
\end{array}\right| + 0 + 0 + (-1)^5(1)\left|\begin{array}{cccc}
0 & 1 & 3 \\
-2 & -3 & -5 \\
4 & -4 & 4
\end{array}\right|
</math>


We would then continue using cofactor expansion on the 3x3 matrices and our problem will only involve taking determinants of 2x2 matrices.


<math>|A| = 2(40) + 0 + 0 - 1(48) = 32.</math>
<math>I = \int x\,\mathrm dx\!+\int\ln{x}\,\mathrm dx\!+\int e^x\,\mathrm dx\!</math>


===#5===
'''...that for every square matrix ''A'' there exists a square matrix ''B'' such that ''AB'' = (|''A''|)*(''I'') is a square matrix where the diagonal entries are all |""A""| and non-diagonal entries are zero.'''


<math>I = (\frac{x^2}{2}+c_1) + \int\ln{x}\,\mathrm dx\! + (e^x +c_3)</math>
Let B be the square matrix with the same dimension as A whose i,j entry is (-1)^(i+j) det(A_{ji}) (called the transpose of the cofactor matrix, or the classical adjoint of A).


Let <math>u = \ln{x}</math> and <math>dv = \mathrm dx\!</math>.
Here is an example with a 2x2 matrix:


Then, <math>du = \frac{1}{x} \mathrm dx\!</math> and <math>v = x</math>.
<math>
A =
\left[\begin{array}{cc}
1 & 4 \\
3 & 2
\end{array}\right],
</math>


So,
|A| = 2 - 12 = -10


<math>I = (\frac{x^2}{2}+c_1) + uv-\int v\,\mathrm du\! + (e^x +c_3)</math>
<math>
A^t =
\left[\begin{array}{cc}
1 & 3 \\
4 & 2
\end{array}\right],
</math>


<math>I = (\frac{x^2}{2}+c_1) + (\ln{x})(x)-\int (x)\,(\frac{1}{x}\mathrm dx\!) + (e^x +c_3)</math>
and the cofactor matrix of A<sup>t</sup> is


<math>I = (\frac{x^2}{2}+c_1) + (\ln{x})(x)-\int \mathrm dx\! + (e^x +c_3)</math>
<math>
B =
\left[\begin{array}{cc}
2 & -4 \\
-3 & 1
\end{array}\right].
</math>


<math>I = (\frac{x^2}{2}+c_1) + (x\ln{x}-x+c_2) + (e^x +c_3)</math>


<math>I = \frac{x^2}{2} + x\ln{x}-x + e^x + C</math>
<math>
AB =
\left[\begin{array}{cc}
1 & 3 \\
4 & 2
\end{array}\right]
\left[\begin{array}{cc}
2 & -4 \\
-3 & 1
\end{array}\right] = \left[\begin{array}{cc}
-10 & 0 \\
0 & -10
\end{array}\right].
</math>

Latest revision as of 15:56, 23 April 2012

Math 163b

[edit]

#1

[edit]

Find .

Let and .

Then, and .

So,

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#2

[edit]

Find .



Let and .

Then, and .

So,