Showing that the candidate basis does span C A Video transcript In the last couple of videos, I already exposed you to the idea of a matrix, which is really just an array of numbers, usually a 2-dimensional array.

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There will not be a lot of details in this section, nor will we be working large numbers of examples. The first special matrix is the square matrix.

In other words, it has the same number of rows as columns.

Vectors and Matrices |
Matrix - Vector Equations A system of linear equations can always be expressed in a matrix form. The matrix version of the equation has its own geometric interpretation. |

Null space and column space |
Prev Section Next 5. Parametric Form of a System Solution We now know that systems can have either no solution, a unique solution, or an infinite solution. |

In a square matrix the diagonal that starts in the upper left and ends in the lower right is often called the main diagonal.

The next two special matrices that we want to look at are the zero matrix and the identity matrix. Here are the general zero and identity matrices. These are matrices that consist of a single column or a single row. Arithmetic We next need to take a look at arithmetic involving matrices.

If it is true, then we can perform the following multiplication. Here are a couple of the entries computed all the way out.

Determinant The next topic that we need to take a look at is the determinant of a matrix. The determinant is actually a function that takes a square matrix and converts it into a number. The actual formula for the function is somewhat complex and definitely beyond the scope of this review. The main method for computing determinants of any square matrix is called the method of cofactors.

We can give simple formulas for each of these cases. There is an easier way to get the same result. A quicker way of getting the same result is to do the following. First write down the matrix and tack a copy of the first two columns onto the end as follows.

What we do is multiply the entries on each diagonal up and the if the diagonal runs from left to right we add them up and if the diagonal runs from right to left we subtract them.

Here is the work for this matrix. Matrix Inverse Next, we need to take a look at the inverse of a matrix. Example 4 Find the inverse of the following matrix, if it exists.

In other words, we want a 1 on the diagonal that starts at the upper left corner and zeroes in all the other entries in the first three columns. If you think about it, this process is very similar to the process we used in the last section to solve systems, it just goes a little farther.

Here is the work for this problem. Example 5 Find the inverse of the following matrix, provided it exists. However, there is no way to get a 1 in the second entry of the second column that will keep a 0 in the second entry in the first column.

We will leave off this discussion of inverses with the following fact. Systems of Equations Revisited We need to do a quick revisit of systems of equations. The solving process is identical. There will be no solutions.An elementary matrix is a square matrix with one arbitrary column, but otherwise ones along the diagonal and zeros elsewhere (i.e., an identify matrix with the exception of one column).

A.3 Linear Programming in Matrix Form We solve a system of linear equations by Gauss-Jordan elimination and find the vector form for the general solution of the system. Will be used in vector space.

Problems in Mathematics. General Solutions of Systems in Vector Form MA We are looking for solutions to the system Ax = b, in column vector form in what follows. We wish to organize the vectors We know that matrix multiplication is linear so we can check out the general solution as follows.

The transpose of a matrix A is obtained by writing the row of A, in order, as columns and denoted by A T. In other words, if A - (A ij), then B = (b ij) is the transpose of A if b ij - a ji for all i and j.

Vectors and Matrices Vectors and Matrices A.2 of matrix multiplication is sometimes referred to as an inner product. It can be visualized by placing the The following properties of matrices can be seen easily by writing out the appropriate expressions in each.

If one converts this row of the matrix back to equation form, the result is which does not make any sense.

Therefore, a system has no solution if a constant appears in a row that has no pivot. Therefore, a system has no solution if a constant appears in a row that has no pivot.

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Vector notation - Wikipedia