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Matrices For grade 1, undergraduate students. Made by Department of Math. ,Anqing Teachers college. Definition. A rectangular array of numbers composed of m rows and n columns is called an matrix (read m by n matrix). We also say that the matrix A is of, or
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Matrices For grade 1, undergraduate students Made by Department of Math. ,Anqing Teachers college
Definition. A rectangular array of numbers composed of m rows and n columns is called an matrix (read m by n matrix). We also say that the matrix A is of, or has, size . 1 Some notations
The elements form the i-th row ofA , and the elements form the j-th column of A. We will often write for A.
Definition. If are matrices, then iff for i=1,2…, m and j=1,…,n.
Definition. If are two matrices, their sum A+B , is the matrix , where i=1,2…, m , j=1,2…,n. .Matrix opertions
Definition. If is an matrix and r is a number then rA, the scalar multipleof A byr, is the matrix where i=1,2…, m and j=1,…,n.
.Some properties Proposition 1. The matrices of size form a vector space under the operations of matrix addition and scalar multiplication. We denote this vector space by Mmn. The dimension of the vector space Mmn is not hard to compute. We take our lead from the method we used to show that dim Rn=n. Introduce the matrix by the requirement
Proposition 2. The vectors form a basis for Mmn . Thereforedim EXAMPLE 1.
2 Matrix products Definition. If is an matrix and is an matrix, their matrix product is the matrix, where
Remark. Note that for the product of A and B to be defined the number of columns of A must be equal to the number of rows of B. Thus the order in which the product of A and B is taken is very important, for AB can be defined without AB being defined.
EXAMPLE 4. Compute the matrix product • Solution.Note the answer is a • matrix
Remark. Note that the product is not defined. EXAMPLE 5. Compute the matrix product
Answer . Definition. A matrix A is said to be a square matrix of size n iff it has n rows and n columns (that is the number of rows equals the number of columns equals n).
Remark. It is easy to see that if A and B are square matrices of size n then the products AB and BA are both defined. However they may not be equal.. EXAMPLE 7. Let Compute the matrix products AB and BA. Solution. We have
and so we see that AB BA. Remark. As the preceding example shows even if AB and BA are defined we should not expect that AB=BA.
Similarly, is defined and denoted by . Notation. If A is a square matrix then AA is defined and is denoted by A2.
EXAMPLE 8. Let Calculate . Solution.We have
.The rules of matrix operations (1) A+B=B+A (2) A+(B+C)=A+(B+C) (3) r(A+B)=rA+rB (4) A+0=A (5) 0A=0 (6) A+(-1)A=0 (7) (r+s)A=rA+sA (8) (A+B)·C=A·C+C·B (9) 0·A=0=A·0 (10) A·(B·C)=(A·B) ·C
3 Special types of matrices Diagonal matrices.
is a lower triangular matrix. Triangular matrices. A square matrix A is said to be lower triangular iff A= where if For example
The Zero matrix. The zero matrix is the matrix 0 all of those entries are 0. Idempotent matrices. A square matrix A is said to be idempotent iff Nilpotent matrices. A square matrix A is said to be nilpotent iff there is an integer q such .
Denoted by . Nonsingular matrices. A square matrix A is said to be invertible or nonsingular iff there exists a matrix B such that AB=I and BA=I. For example if then
A nilpotent matrix is not invertible. For suppose that A is a nilpotent matrix that is invertible. Let B be an inverse for A. Since A is nilpotent there is an integer q such that Then so If we repeat this trick q-1 times we will get
But then which is impossible. Symmetricand skew-symmetric matrices. A square matrix A= is said to symmetric iff for it is said to be skew-symmetric iff for
For example are symmetric matrices, and are skew-symmetric matrices.
Proposition 3 A matrix is nonsingular iff If then
PROOF. Suppose that Let Then
Suppose conversely that A is nonsingular, but that . We will deduce a contradiction. Let and therefore A is nonsingular with
Then computing as above This gives the equation Therefore
So and hence 1=0, which is impossible. So that But then A=0 also, so
4 SOME EXERCISES 1. Perform the following matrix multiplications
2. Which of the following matrices are nonsingular, idempotent, nilpotent, symmetric, or skew-symmetric?
3. If A is an idempotent square matrix show I-2A is invertible (Hint: Idempotent correspond to projections. Interpret I-2A as a reflection. Try the case first. Then try to generalize.) Thanks!!!