Special Matrices:
Triangular, Symmetric, Diagonal
We have seen that a matrix is a block of entries or two dimensional data. The size of the matrix is given by the number of rows and the number of columns. If the two numbers are the same, we called such matrix a square matrix.
To square matrices we associate what we call the main diagonal (in short the diagonal). Indeed, consider the matrix
Its diagonal is given by the numbers a and d. For the matrix
its diagonal consists of a, e, and k. In general, if A is a square matrix of order n and if a_{ij} is the number in the i^{th}row and j^{th}colum, then the diagonal is given by the numbers a_{ii}, for i=1,..,n.
The diagonal of a square matrix helps define two type of matrices: uppertriangular and lowertriangular. Indeed, the diagonal subdivides the matrix into two blocks: one above the diagonal and the other one below it. If the lowerblock consists of zeros, we call such a matrix uppertriangular. If the upperblock consists of zeros, we call such a matrix lowertriangular. For example, the matrices
are uppertriangular, while the matrices
are lowertriangular. Now consider the two matrices
The matrices A and B are triangular. But there is something special about these two matrices. Indeed, as you can see if you reflect the matrix A about the diagonal, you get the matrix B. This operation is called the transpose operation. Indeed, let A be a nxm matrix defined by the numbers a_{ij}, then the transpose of A, denoted A^{T} is the mxn matrix defined by the numbers b_{ij} where
b_{ij} = a_{ji}. For example,
for the matrix
we have
Properties of the Transpose operation. If X and Y are mxn matrices and Z is an nxk matrix, then
 1.

(X+Y)^{T} = X^{T} + Y^{T}
 2.

(XZ)^{T} = Z^{T} X^{T}
 3.

(X^{T})^{T} = X
A symmetric matrix is a matrix equal to its transpose. So a symmetric matrix must be a square matrix. For example, the matrices
are symmetric matrices. In particular a symmetric matrix of order n, contains at most
different numbers.
A diagonal matrix is a symmetric matrix with all of its entries equal to zero except may be the ones on the diagonal.
So a diagonal matrix has at most n different numbers other than 0. For example, the matrices
are diagonal matrices. Identity matrices are examples of diagonal matrices. Diagonal matrices play a crucial role in matrix theory. We will see this later on.
Example. Consider the diagonal matrix
Define the powermatrices of A by
Find the power matrices of A and then evaluate the matrices
for n=1,2,....
Answer. We have
and
By induction, one may easily show that
for every natural number n. Then we have
for n=1,2,..
Scalar Product. Consider the 3x1 matrices
The scalar product of X and Y is defined by
In particular, we have
X^{T}X = (a^{2} + b^{2} + c^{2}). This is a 1 x 1 matrix .
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