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Study Guide for Matrices - Linear Algebra | MATH 300, Study notes of Linear Algebra

Material Type: Notes; Professor: Konieczny; Class: Linear Algebra; Subject: Mathematics; University: University of Mary Washington; Term: Unknown 1989;

Typology: Study notes

2009/2010

Uploaded on 02/24/2010

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Math 300
Notes for Section 2.1
1. (Matrices). An mnmatrix Ais a rectangular array of numbers arranged in mhorizontal rows
and nvertical columns:
AD
2
6
6
6
4
a11 a12 ::: a1n
a21 a22 ::: a2n
:
:
::
:
::
:
:
am1 am2 ::: amn
3
7
7
7
5
:
We say thatAis of size mby n. The number aij in the ith row and jth column of Ais called the
.i;j/entry of Aand we write
ADŒaij :
If mDn, we say that Aisasquare matrix of order n.
2. (Equality of Matrices). Two matrices are said to be equal if they have the same size and their
corresponding entries are equal.
3. (Matrix Addition and Subtraction). If ADŒaij and BDŒbij are matrices of the same size,
then the sum ACBand difference ABare defined by:
ACBDŒaij Cbij (add corresponding entries);
ABDŒaij bij (subtract corresponding entries):
Matrices of different sizes cannot be added or subtracted.
4. (Scalar Multiplication). If ADŒaij is a matrix and cis a scalar, then the scalar multiple cA is
defined by:
cA DŒcaij (multiply each entry by c):
5. (Matrix Multiplication). If ADŒaij is an mnmatrix and BDŒbij is a npmatrix, then
the product AB is the mpmatrix whose entries are determined as follows. To find the entry in
the row iand column jof AB:
(a) Single out row ifrom Aand column jfrom B.
(b) Multiply the corresponding entries from the row and column together and then add up the
resulting products.
Symbolically, AB DŒcij , where
cij Dai1b1j Cai2b2j CCainbnj D
n
X
kD1
aikbkj :
1
pf2

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Math 300

Notes for Section 2.

  1. ( Matrices ). An m  n matrix A is a rectangular array of numbers arranged in m horizontal rows

and n vertical columns :

A D

a 11 a 12 : : : a 1n

a 21 a 22 : : : a2n

a m a m : : : a mn

We say that A is of size m by n. The number a ij in the i th row and j th column of A is called the

.i; j / entry of A and we write

A D Œa ij

If m D n, we say that A is a square matrix of order n.

  1. ( Equality of Matrices ). Two matrices are said to be equal if they have the same size and their

corresponding entries are equal.

  1. ( Matrix Addition and Subtraction ). If A D Œaij  and B D Œbij  are matrices of the same size,

then the sum A C B and difference A  B are defined by:

A C B D Œaij C bij  (add corresponding entries);

A  B D Œa ij  b ij  (subtract corresponding entries):

Matrices of different sizes cannot be added or subtracted.

  1. ( Scalar Multiplication ). If A D Œa ij  is a matrix and c is a scalar, then the scalar multiple cA is

defined by:

cA D Œca ij  (multiply each entry by c):

  1. ( Matrix Multiplication ). If A D Œa ij  is an m  n matrix and B D Œb ij  is a n  p matrix, then

the product AB is the m  p matrix whose entries are determined as follows. To find the entry in

the row i and column j of AB:

(a) Single out row i from A and column j from B.

(b) Multiply the corresponding entries from the row and column together and then add up the

resulting products.

Symbolically, AB D Œc ij , where

c ij D a i b 1j C a i b 2j C    C a in b nj

D

n X

kD 1

a ik b kj

  1. ( Matrix Form of a Linear System ). Consider a linear system with m equations and n unknowns:

a 11 x 1 C a 12 x 2 C : : : C a1nxn D b 1

a 21 x 1 C a 22 x 2 C : : : C a 2n x n D b 2

a m x 1 C a m x 2 C    C amnxn D bm:

Define the following matrices:

A D

a 11 a 12 : : : a 1n

a 21 a 22 : : : a 2n

a m a m : : : a mn

; xE D

x 1

x 2

x n

E

b D

b 1

b 2

b m

The matrix A is called the coefficient matrix of the linear system (1). Verify that

A xE D

a 11 a 12 : : : a 1n

a 21 a 22 : : : a 2n

am1 am2 : : : amn

x 1

x 2

xn

D

a 11 x 1 C a 12 x 2 C : : : C a 1n x n

a 21 x 1 C a 22 x 2 C : : : C a 2n x n

am1x 1 C am2x 2 C    C amnxn

Therefore, the linear system (1) can be written as a single matrix equation:

AxE D

E

b (matrix form of a linear system).

Let aE 1 ; : : : ; aE n be the columns of A. Then

AxE D x 1 aE 1 C x 2 Ea 2 C    C xn aEn:

Hence the system AxE D

E

b is consistent if and only if

E

b is a linear combination of the columns

of A.