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Linear Algebra, Theory And Applications, 2012a

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Matrices <strong>And</strong> <strong>Linear</strong><br />

Transformations<br />

2.1 Matrices<br />

You have now solved systems of equations by writing them in terms of an augmented matrix<br />

and then doing row operations on this augmented matrix. It turns out that such rectangular<br />

arrays of numbers are important from many other different points of view. Numbers are<br />

also called scalars. In general, scalars are just elements of some field. However, in the first<br />

part of this book, the field will typically be either the real numbers or the complex numbers.<br />

A matrix is a rectangular array of numbers. Several of them are referred to as matrices.<br />

For example, here is a matrix. ⎛<br />

⎝ 1 5 2 2 3 8 4<br />

7<br />

⎞<br />

⎠<br />

6 −9 1 2<br />

This matrix is a 3 × 4 matrix because there are three rows and four columns. ⎛ The ⎞ first<br />

1<br />

rowis(1234), the second row is (5 2 8 7) and so forth. The first column is ⎝ 5 ⎠ . The<br />

6<br />

convention in dealing with matrices is to always list the rows first and then the columns.<br />

Also, you can remember the columns are like columns in a Greek temple. They stand up<br />

right while the rows just lay there like rows made by a tractor in a plowed field. Elements of<br />

the matrix are identified according to position in the matrix. For example, 8 is in position<br />

2, 3 because it is in the second row and the third column. You might remember that you<br />

always list the rows before the columns by using the phrase Rowman Catholic. The symbol,<br />

(a ij ) refers to a matrix in which the i denotes the row and the j denotes the column. Using<br />

this notation on the above matrix, a 23 =8,a 32 = −9,a 12 =2, etc.<br />

There are various operations which are done on matrices. They can sometimes be added,<br />

multiplied by a scalar and sometimes multiplied. To illustrate scalar multiplication, consider<br />

the following example.<br />

⎛<br />

⎞ ⎛<br />

⎞<br />

1 2 3 4 3 6 9 12<br />

3 ⎝ 5 2 8 7 ⎠ = ⎝ 15 6 24 21 ⎠ .<br />

6 −9 1 2 18 −27 3 6<br />

The new matrix is obtained by multiplying every entry of the original matrix by the given<br />

scalar. If A is an m × n matrix −A is defined to equal (−1) A.<br />

Two matrices which are the same size can be added. When this is done, the result is the<br />

37

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