259 Lecture 14

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# 259 Lecture 14 - PowerPoint PPT Presentation

259 Lecture 14. Elementary Matrix Theory. A matrix is a rectangular array of elements (usually numbers) written in rows and columns. Example 1: Some matrices:. Matrix Definition. Matrix Definition. Example 1 (cont.): Matrix A is a 3 x 2 matrix of integers.

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### 259 Lecture 14

Elementary Matrix Theory

A matrix is a rectangular array of elements (usually numbers) written in rows and columns.

Example 1: Some matrices:

Matrix Definition
Matrix Definition
• Example 1 (cont.):
• Matrix A is a 3 x 2 matrix of integers.
• A has 3 rows and 2 columns.
• Matrix B is a 2 x 2 matrix of rational numbers.
• Matrix C is a 1 x 4 matrix of real numbers.
• We also call C a row vector.
• A matrix consisting of a single column is often called a column vector.
Arithmetic with Matrices
• Matrices of the same size (i.e. same number of rows and same number of columns), with elements from the same set, can be added or subtracted!
• The way to do this is to add or subtract corresponding entries!
Arithmetic with Matrices
• Example 2: For matrices A and B given below, find A+B and A-B.
Arithmetic with Matrices
• Example 2 (cont):

Solution:

• Note that A+B and A-B are the same size as A and B, namely 2 x 3.
Arithmetic with Matrices
• Matrices can also be multiplied. For AB to make sense, the number of columns in A must equal the number of rows in B.
Arithmetic with Matrices
• Example 3: For matrices A and B given below, find AB and BA.
Arithmetic with Matrices
• Example 3 (cont.):
• A x B is a 3 x 2 matrix. To get the row i, column j entry of this matrix, multiply corresponding entries of row i of A with column j of B and add.
• Since B has 2 columns and A has 3 rows, we cannot find the product BA (# columns of 1st matrix must equal # rows of 2cd matrix).
Arithmetic with Matrices
• Another useful operation with matrices is scalar multiplication, i.e. multiplying a matrix by a number.
• For scalar k and matrix A, kA=Ak is the matrix formed by multiplying every entry of A by k.
Identities and Inverses
• Recall that for any real number a,

a+0 = 0+a = a and (a)(1) = (1)(a) = a.

• We call 0 the additive identity and 1 the multiplicative identity for the set of real numbers.
• For any real number a, there exists a real number –a, such that

a+(-a) = -a+a = 0.

• Also, for any non-zero real number a, there exists a real number a-1 = 1/a, such that

(a-1)(a) = (a)(a-1) = 1.

• We all –a and a-1 the additive inverse and multiplicative inverse of a, respectively.
Identities and Inverses
• For matrices, we also have an additive identity and multiplicative identity!
Identities and Inverses

A+0 = 0+A = A and AI = IA = A holds.

(HW-check!)

Identities and Inverses
• Clearly, A+(-A) = -A + A = 0 follows! Note also that B-A = B+(-A) holds for any m x n matrices A and B.
Identities and Inverses
• Example 5 (cont):
Identities and Inverses
• Example 5 (cont.)
Identities and Inverses
• Example 5 (cont.)
Identities and Inverses
• Example 5 (cont):
Identities and Inverses
• For multiplicative inverses, more work is needed.
• For example, here is one way to find the matrix A-1, given matrix A, in the 2 x 2 case!
Identities and Inverses
• From the first matrix equation, we see that e, f, g, and h must satisfy the system of equations:
• ae + bg = 1

af + bh = 0

ce + dg = 0

cf + dh = 1.

• It follows that if e, f, g, and h satisfy this system, then the second matrix equation above also holds!
• Solving the system of equations, we find that ad-bc  0 must hold and

• Thus, we have the following result for 2 x 2 matrices:
Identities and Inverses
• In this case, we say A is invertible.
• If ad-bc = 0, A-1 does not exist and we say A is not invertible.
• We call the quantity ad-bc the determinant of matrix A.
Identities and Inverses
• Example 6: For matrices A and B below, find A-1 and B-1, if possible.
Identities and Inverses
• Example 6 (cont.)
• Solution: For matrix A, ad-bc = (1)(4)-(2)(3)= 4-6 = -2 0, so A is invertible. For matrix B, ad-bc = (3)(2)-(1)(6) = 6-6 = 0, so B is not invertible.
• HW-Check that AA-1 = A-1A = I!!
• Note: For any n x n matrix, A-1 exists, provided the determinant of A is non-zero.
Linear Systems of Equations
• One use of matrices is to solve systems of linear equations.
• Example 7: Solve the system

x + 2y = 1

3x + 4y = -1

• Solution: This system can be written in matrix form AX=b with:
Linear Systems of Equations
• Example 7 (cont.)
• Since we know from Example 6 that A-1 exists, we can multiply both sides of AX = b by A-1 on the left to get:

A-1AX = A-1b => X = A-1b.

• Thus, we get in this case:
Linear Systems of Equations
• Example 7 (cont.):
References
• Elementary Linear Algebra (4th ed) by Howard Anton.
• Cryptological Mathematics by Robert Edward Lewand (section on matrices).