NOTES ON LINEAR ALGEBRA

 

CONTENTS:

[1] MULTIPLYING MATRICES

[2] GAUSSIAN ELIMINATION

[3] INVERTING MATRICES

 

 

[1] MULTIPLYING MATRICES:

 

For ease of presentation, I will NOT draw the parentheses around the matrices correctly. If I were to, I’d have to use either the Equation Editor (which takes more time) or LaTeX (which your computer has trouble reading).

 

Let’s say we have the matrix A =

 

            (1 2)

            (3 4)

 

And we want to multiply it by the column vector v =

 

            (5)

            (6)

 

The answer is Av =

 

            (1 2) (5)       (1*5 + 2*6)      (17)

            (3 4) (6)   =  (3*5 + 4*6)  =  (39)

 

 

Let’s do another example. Let B =

 

            (2 7)

            (3 5)

 

and let the vector w =

 

            (1)

            (3)

 

 

Then B w =

 

            (2 7) (1)       (2*1 + 7*3)      (23)

            (3 5) (3)   =  (3*1 + 5*3)  =  (18)

 

 

Let’s study a bigger matrix now. Let C =

 

            (1 2)

            (3 4)

            (5 6)

 

and consider the vector x =

 

            (2)

            (1)

 

Then C x =

 

            (1 2)     (2)          (1*2 + 2*1)        ( 4 )

            (3 4)     (1)     =   (3*2 + 4*1)   =   (10)

            (5 6)                    (5*2 + 6*1)        (16)

 

And finally, let’s look at D =

 

            (1 2 0)

            (3 4 2)

            (5 6 3)

 

and the vector y =

 

            (1)

            (0)

            (2)

 

Then the product D y =

 

            (1 2 0)  (1)      (1*1 + 2*0 + 0*2)

            (3 4 2)  (0)  =  (3*1 + 4*0 + 2*0)

            (5 6 3)  (2)      (5*1 + 6*0 + 3*2)

 

 

 

This is basically how to multiply a matrix by a column vector. Now we want to study how to multiply two matrices together. We have the following rule, which we proved:

 

Matrix Multiplication Rule:

          Let’s say A has Ra rows and Ca columns, and B has Rb rows and Cb columns. This means A is an Ra x Ca matrix, and B is an

Rb x Cb matrix. Then we can do the multiplication AB if and only if Ca = Rb, and the resulting matrix AB has Ra rows and Cb columns.

 

For example, if A is 3x4 and B is 4x2, then we can do the multiplication AB, and the product AB is a 3x2 matrix; however, we cannot do the multiplication BA, for 2 ¹ 3.

 

 

Let’s do some examples: Let the matrices A and B be (respectively)

 

          (1 2)            and              (5 6)

          (3 4)                               (7 8)

 

Then in this case we can multiply in EITHER order, as both are 2x2. Let’s do AB =

 

          (1 2)  (5 6)

          (3 4)  (7 8)

 

The way we multiply matrices is column by column. To find the first column in the product, we multiply the matrix A by the first column of B, and that’s the answer. To find the second column of the product, we multiply A by the second column of B.

 

Step 1: Finding the first column of the product:

          (1 2)  (5)      (1*5 + 2*7)      (19)

          (3 4)  (7)  =  (3*5 + 4*7)  =  (43)

 

Step 2: Finding the second column of the product:

          (1 2)  (6)      (1*6 + 2*8)      (22)

          (3 4)  (8)  =  (3*6 + 4*8)  =  (50)

 

Step 3: Combining the above:

 

          (1 2)  (5 6)      (19 22)

          (3 4)  (7 8)  =  (43 50) 

 

Let’s do a harder one: Let the matrices C and D be (respectively)

 

          (1 2 3)                  (3 0)

          (4 5 6)         and    (1 2)

          (2 1 0)                  (0 5)

 

First, let’s check and make sure we can multiply CD. C is 3x3, D is 3x2, so yes we can, and the product will be 3x2.

 

Step 1: C times the first column of D gives the first column of CD

 

          (1 2 3)   (3)      (1*3 + 2*1 + 3*0)                ( 5)

          (4 5 6)   (1)  =  (4*3 + 5*1 + 6*0)    =        (17)

          (2 1 0)   (0)      (2*3 + 1*1 + 0*0)               ( 7)

 

Step 2: C times the second column of D gives the second column of CD

 

          (1 2 3)   (0)      (1*0 + 2*2 + 3*5)                (19)

          (4 5 6)   (2)  =  (4*0 + 5*2 + 6*5)    =        (40)

          (2 1 0)   (5)      (2*0 + 1*2 + 0*5)               (  2)

 

Step 3: Combining the above yields CD =

 

          (1 2 3)  (3 0)         (5   19)

          (4 5 6)  (1 2)    =   (17 40)

          (2 1 0)  (0 5)         ( 7   2 )

 

 

 

 

 

 

 

 

[2] GAUSSIAN ELIMINATION:

 

Matrices can be used to represent systems of equations, which we then try to solve. For example, let’s say we have the two equations:

 

          3x + 2y = 5

          4x + 5y = 7

 

Then we can write this in matrix form by

 

          (3 2) (x)      (5)

          (4 5) (y)  =  (7)

 

Or, if we had the three equations

 

          3x + 2y + 5z = 8

          2x + 2y + 4z = 7

          7x + 9y + 0z = 1

 

Then we can write this in matrix form by

 

          (3 2 5) (x)      (8)

          (2 2 4) (y)  =  (7)

          (7 9 0) (z)      (1)

 

Now, we want to find a way to solve such systems of equations. Let’s start with an easy example:

 

          1x + 2y = 1

          3x + 7y = 2

 

We can write this in matrix form by

 

          (1 2) (x)      (1)

          (3 7) (y)  =  (2)

 

Now, let’s look at the two equations. If we multiply the first equation by -3 we get: -3x -6y = -3. If we then add this to the second equation (3x + 7y = 2) we get a new second equation:

 

                     3x + 7y =   2

+                 -3x  - 6y  = -3

                   ------------------

                     0x  + 1y = -1

 

So now we have the two equations

 

          1x + 2y =  1

          0x + 1y = -1

 

which we can write in matrix form as

 

          (1 2) (x)      ( 1)

          (0 1) (y)  =  (-1)

 

We started with the matrix

 

          (1 2) (x)      (1)

          (3 7) (y)  =  (2)

 

If we multiply the first row by -3 and add that to the second row, we get the matrix

 

          (1 2)

          (0 1)

 

And if we multiply 1 by -3 and add it to 2 we get the vector

 

          ( 1)   

          (-1)

 

So we see we can symbolically represent multiplying and adding equations by multiplying and adding rows. Slowly, here goes:

 

 

The goal is to reduce the matrix to something easy to work with, namely something with all zeros below the diagonal.

 

We start with

 

          (1 2) (x)      (1)

          (3 7) (y)  =  (2)

 

Step 1: What do we need to multiply the first row by to cancel the 3 in the second row? Or, find ‘a’ such that 1a + 3 = 0, hence a = -3. We then multiply the first row by -3, and write the result under the second row.

Question 1: why do we multiply the first row by -3? Because that’s what we need to cancel the 3 in the second row.

Question 2: why do we write the result under the second row? Because

that’s where we’re adding the result.

Remember, you must also multiply 1 by -3 and add it to 2. Why? Equality: whatever you do to one side of the equation, you must do to the other.

 

[-3]

          (1 2) (x)      (1)

          (3 7) (y)  =  (2)

           -3  -6                     -3

 

          (1 2) (x)      ( 1)

          (0 1) (y)  =  (-1)

 

Step 2: We can now read off the answers! The two equations are:

 

          1x + 2y = 1

          0x + 1y = -1

 

So we learn from the second equation that y = -1. We then substitute that value into the first equation and get 1x + 2(-1) = 1, so x = 3. We can check this by substituting these values for x and y into the original equations:

         

          1x + 2y = 1  è      1(3) + 2(-1) = 1    

          3x + 7y = 2  è      3(3) + 7(-1) = 2

 

So yes, these values work.

 

Let’s do a slightly harder example.

 

Consider the following:

 

          (1 2 3) (x)    (  2)

          (2 3 0) (y)  = (  1)

          (3 0 1) (z)      (10)

 

Step 1: we want to get a matrix that has all zeros under the diagonal. So we need to get rid of the 2 in the second row and the 3 in the third row. To get rid of the 2 in the second row, we multiply the first row by -2 and add the result to the second row; we multiply the first row by -3 and add the result to the third row. Remember, we write the results of the multiplication under the row we’re going to add it to, and remember we MUST also do the multiplication on the right hand side. So we must multiply 1 by -2 and we must multiply 10 by -3.

 

          (1 2 3) (x)    ( 2)

[-2]      (2 3 0) (y)  = ( 1)

                 -2 -4 -6                  -4

[-3]      (3 0 1) (z)     (10)

                 -3 -6 -9                  -6           

 

This gives

 

          (1  2   3)(x)       (2)

          (0 -1 -6)(y)   =  (-3)

          (0 -6 -8)(z)       ( 4)

 

We’re almost there – we now need to get rid of the -6 in the third row. Then we’ll have a matrix with all zeros under the main diagonal, and we’ll be able to read off the answers.

 

Step 2: We need to get rid of the -6 in the third row. There’s nothing we can multiply the first row by. Why? If we add copies of the first row to the third, we’ll lose the 0 which starts off the third row. What we should do is multiply the second row by something and add it to the third, as this way we won’t lose the zero. So, we need to find ‘a’ such that (-1)a + (-6) = 0, hence a = -6.

 

          (1  2   3)(x)       (2)

          (0 -1 -6)(y)   =  (-3)

[-6]      (0 -6 -8)(z)       ( 4)

                  0    6  36                    18

 

This yields

 

          (1  2   3)(x)       ( 2)

          (0 -1 -6)(y)   =  (-3)

          (0  0 28)(z)       (22)

 

Step 3: We can now read off the answers! The three equations are

 

          1x + 2y + 3z  = 2

          0x  - 1y  - 6z  = -3

          0x  + 0y +28z = 22

 

So z = 22/28  = 11/14

So -y - 6(11/14) = -3 è y = -24/14

So x + 2(-24/14) + 3(11/14) = 2 è x = 43/14

 

Let’s check these numbers in the original equations:

 

          1x + 2y + 3z = 2  è  1(43/14) + 2(-24/14) + 3(11/14) = 2

          2x + 3y + 0z = 1  è  2(43/14) + 3(-24/14) + 0(11/14) = 1

          3x + 0y + 1z = 10 è 3(43/14) + 0(-24/14) + 1(11/14) = 10

 

So we see we do obtain the correct answer! (If it makes you feel better, I got wrong answers the first two times I did the problem – I did the algebra wrong).

 

 

 

 

 

 

 

 

 

 

[3] INVERTING MATRICES:

 

We’re now ready to use the method of Gaussian Elimination to invert matrices. Let’s review how Gaussian Elimination works. We start off with a matrix A and we do row operations to it. This is equivalent to multiplying A by several matrices E1, E2, ..., En (say).

 

For simplicity, let’s assume it takes 5 steps to Gaussian Eliminate A to the Identity matrix, so E5 E4 E3 E2 E1 A = I. Then E5 E4 E3 E2 E1 = A-1, the inverse matrix to A.

 

To keep track of these steps, we can just form E5 E4 E3 E2 E1 I, which by the above is A-1.

 

An example should illustrate.

 

Let’s try to find the inverse to A =

 

          (1 2)

          (3 5)

 

THE GOAL: We will use Gaussian Elimination to get A to the identity matrix (ones on the main diagonal, zeros elsewhere). We will keep track of the Gaussian Elimination by acting on the Identity matrix.

 

Step 1: Write the matrix A followed by the identity:

 

          (1 2)            (1 0)

          (3 5)            (0 1)

 

Step 2: We need to eliminate the 3 in the second row, so we must find ‘a’ such that 1a + 3 = 0.  Hence a = -3. So we multiply the first row of A by -3 and add it to the second row. And remember, by EQUALITY, we must do the same to the other side, to the Identity.

 

          (1 2)            (1 0)

[-3]      (3 5)            (0 1)

           -3 -6                      -3  0   

 

 

          (1   2)          (1  0)

          (0 -1)           (-3 1)

 

 

 

Step 3: Now, we want to have all 1s along the main diagonal, so we might as well adjust the second row right now. We have a -1, where we want a 1. So we must multiply the second row by -1. Again, must do this to both sides:

 

          (1   2)          (1  0)

          (0 -1)           (-3 1)

                  0    1                        3   -1

 

Hence we get

 

          (1 2)            (1  0)

          (0 1)            (3 -1)

 

Step 4: Now we need to get rid of the 2 in the first row, so we multiply the second row by -2 and get:

 

          (1 2)            (1  0)

           0  -2                         -6   2

          (0 1)            (3 -1)

 

and we get

 

          (1 0)            (-5 2)

          (0 1)            ( 3 -1)

 

Note: as a check, you can go thru and see that

 

          (-5  2)

          ( 3  -1)

 

is the inverse to A.

 

 

Let’s do one more problem. Let’s find the inverse for B =

 

          (9 4)

          (7 3)

 

Step 1: Write the matrix B followed by the Identity:

 

          (9 4)            (1 0)

          (7 3)            (0 1)

 

Step 2: What should we multiply the first row by to get rid of the 7 in the second row? So, find ‘a’ such that 9a + 7 = 0, or a = -7/9.

 

          (9 4)            (1  0)

[-7/9]    (7 3)            (0  1)

           -7  -28/9 -7/9  0

 

And we get

 

          (9     4)                  (1     0)

          (0 -1/9)                  (-7/9 1)

 

Step 3: We want to end up with the identity matrix on the left. We have -1/9 in the lower diagonal – we need to multiply the second row by -9 to get 1.

 

          (9     4)                  (1     0)

[-9]      (0 -1/9)                  (-7/9 1)

            0       1                                      7     -9

 

And we get

 

          (9 4)                      (1   0)

          (0 1)                      (7  -9)

 

 

 

 

 

 

Step 4: We need to get rid of the 4 in the first row, so we multiply the second row by -4 and add it to the first

 

[-4]      (9 4)                      (1   0)

            0 -4                                        -28  36

          (0 1)                      (7  -9)

 

And we get

 

          (9 0)            (-27 36)

          (0 1)            (  7   -9)      

 

Step 5: We need to have the identity on the left. We have a 9 in the upper left corner, so we must multiply the first row by 1/9.

 

[1/9]     (9 0)            (-27 36)

            1  0                           -3       4

(0 1)            (  7   -9)      

 

And we get

 

          (1 0)            (-3 4)

          (0 1)             ( 7 -9)

 

You can check that this is the inverse of B by doing the multiplication.