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|{z} ncolumns whereaijis the number corresponding to theithrow andjthcolumn.iis the row subscript and jis the column subscript. {Thesizeof the matrix ismxn. {Matrices are denoted by capital letters:A,B,C, etc. {Ifm=n, then the matrix is said to besquare. {For a square matrix,a11,a22,a33, ...,annis called themain diagonal. {tr(A) denotes thetraceofAwhich is the sum of the diagonal elements. For example, if A=2
3 23
5 {Arow vectoris a matrix with only 1 row, i.e., it has size 1xn. Example:
3 12
4 0 2 and
3 12
Scalar Multiplication:Example, 2A. In order to do scalar multiplication, multiply all entries by the scalar. For example, using the matrixAfrom above, i.e.,
Linear Combination:IfA1,A2, ...,Anare matrices of the same size andc1,c2, ...,cnare scalars, then c
3 12 +0 51 1 04
69 12
9 36 +0 51 1 04
Properties of Matrix Addition and Substraction:LetA,BandCbemxnmatrices andcand dbe scalars, then
then A T=1 3 21
0 5 323
5 {Notice that ifAismxn, thenATisnxm. {Some Properties of Transposes
5 andB=2 431
0 1 5 43 5
{ Zero Matrix Thezero matrixis denoted byOorOmxnwhereOis a matrix of sizemxn. This is simply a matrix with all zeros. Example: O=0 0 0 0 ;orO=2 40 0
0 0 0 03 5
3:00 2:753 5 = 120(2:00) + 250(3:00) + 305(2:75) = 1828:75:
3:00 2:753 5 = 207(2:00) + 140(3:00) + 419(2:75) = 1986:25:
3:00 2:753 5 = 29(2:00) + 120(3:00) + 190(2:75) = 940:50: What we just did was matrix multiplication. We multiplied a 3x3 matrix by a 3x1 matrix to get a 3x1 matrix: 2
42:00
3:00 2:753 5 =2
3 4 1 63 5 ,B=2 401 0
4 0 2 81 73
5 { Properties of Matrix Multiplication:LetA,B, andCbe matrices of appropriate size for matrix multiplication andcbe a scalar, then the following properties hold.
5 ;B=2 446 3
5 4 4
5 ndACandBC. You will notice they are equal even thoughA6=B. { Properties for the Identity Matrix
[PDF] produit de 3 matrices
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Matrices and Matrix Operations
Linear Algebra
MATH 2010
Basic Denition and Notation for Matrices
{Ifmandnare positive integers, then anmxnmatrixis a rectangular array of numbers (entries) mrows8 >>:2 6 664a11a12a13::: a1n
a21a22a23::: a2n............
a m1am2am3::: amn3 7 775|{z} ncolumns whereaijis the number corresponding to theithrow andjthcolumn.iis the row subscript and jis the column subscript. {Thesizeof the matrix ismxn. {Matrices are denoted by capital letters:A,B,C, etc. {Ifm=n, then the matrix is said to besquare. {For a square matrix,a11,a22,a33, ...,annis called themain diagonal. {tr(A) denotes thetraceofAwhich is the sum of the diagonal elements. For example, if A=2
43 5 2
01 43 1 23
5 then the diagonal elements are 3, -1, and 2, so tr(A) = 3 + (1) + 2 = 4 {Acolumn vectoris a matrix with only 1 column, i.e., it has sizemx1. Example: 2 413 23
5 {Arow vectoris a matrix with only 1 row, i.e., it has size 1xn. Example:
01 2 8
{Two matrices areequalif they are the same size and all the entries are the exact same. For example, if A=2 4 1 3 andB=a4 1b what doaandbhave to equal forA=B? Adding and Subtracting Matrices: IMPORTANT!!! In order to add/subtract matrices, matrices must be theSAMEsize. If two matrices are the same size, then to add (subtract) them, we simply add (subtract) corresponding elements. LetA=2 1 1
11 4 andB=23 4 3 12 ThenA+B=2 1 1
11 4 +23 43 12
2 + 2 1 + (3) 1 + 4
1 + (3)1 + 1 4 + (2)
42 54 0 2 and
AB=2 1 1
11 4 23 43 12
22 1(3) 14
1(3)11 4(2)
0 43 22 6Scalar Multiplication:Example, 2A. In order to do scalar multiplication, multiply all entries by the scalar. For example, using the matrixAfrom above, i.e.,
A=2 1 1
11 4 we can calculate 2Aas2A=2(2) 2(1) 2(1)
2(1) 2(1) 2(4)
=4 2 2 22 8Linear Combination:IfA1,A2, ...,Anare matrices of the same size andc1,c2, ...,cnare scalars, then c
1A1+c2A2+:::+cnAn
is called alinear combinationofA1,A2, ...,Anwith coecientsc1,c2, ...,cn. For example, ifA=2 1 1
11 4 ; B=23 4 3 12 ; C=0 51 1 04 then2A3B+C= 22 1 1
11 4 323 43 12 +0 51 1 04
2(2) 2(1) 2(1)
2(1) 2(1) 2(4)
3(2) 3(3) 3(4)
3(3) 3(1) 3(2)
+0 51 1 04 4 2 2 22 869 12
9 36 +0 51 1 04
46 + 0 2(9) + 5 212 + (1)
2(9) + 123 + 0 8(6) + (4)
2 1611
85 10Properties of Matrix Addition and Substraction:LetA,BandCbemxnmatrices andcand dbe scalars, then
1.A+B=B+ACommutative Property of Addition
2.A+ (B+C) = (A+B) +CAssociative Property of Addition
3. (cd)A=c(dA) Associative Property of Scalar Multiplication
4. 1A=AMultiplicative Identity
5.c(A+B) =cA+cBDistributive Property
6. (c+d)A=cA+dADistributive Property
Transposes:
{The transpose of a matrix is denotedAT. To nd the transpose of a matrix, you interchange the rows and columns. In other words, you can think about it as write all the rows as columns or all the columns as rows. For example, if A=1 2 31then A T=1 3 21
Find the transpose of
A=2 41 20 5 323
5 {Notice that ifAismxn, thenATisnxm. {Some Properties of Transposes
1. (AT)T=A
2. (A+B)T=AT+BT
3. (cA)T=cAT
{A matrix is said to besymmetricifA=AT.Sample Problems:
1. Let
A=21 5
0 3 5FindAT.
2. Let
A=241 2 3
0 5 4 32 135 andB=2 431
0 1 5 43 5
Find (A+ (2B)T)T.
3. Findcanddso that
A=241 2 5
2 3c d4 03 5 is symmetric.Special Matrices:There are two special matrices,
{ Identity Matrixis denoted byIorInwherendenotes a square matrix of sizenxn. The identitity matrix is a square matrix with 1's on the diagonal and 0's as all other elements: I 2=1 0 0 1 ; I 4=2 6641 0 0 0
0 1 0 0
0 0 1 0
0 0 0 13
7 75{ Zero Matrix Thezero matrixis denoted byOorOmxnwhereOis a matrix of sizemxn. This is simply a matrix with all zeros. Example: O=0 0 0 0 ;orO=2 40 0
0 0 0 03 5
Properties of the Zero Matrix
1.A+O=Awhere it is understood thatOhas the same size asA.
2.A+ (A) =O
3. IfcA=O, thenc= 0 orA=O.
Matrix Multiplication:Matrix multiplication is more involved. You canNOTmultiply correspond- ing entries!! {To help understand the process of matrix multiplication, we will rst examine an applied problem which uses the same strategy as is used in matrix multiplication. Assume you are at a football stadium where there are three dierent refreshment centers, the south stand, north stand and west stand. At each stand, they are selling peanuts, hot dogs and soda. See the gure below. Assume you want to know how much total the south stand made. You need to multiply the number of each of the items sold by the south stand (in the rst row of the matrix) by the selling price of each item (given in the column vector containing selling price). In other words, you need to isolate the rst row and multiply by the corresponding items in the column and then add:120 250 3052
42:003:00 2:753 5 = 120(2:00) + 250(3:00) + 305(2:75) = 1828:75:
So, the south stand sold a total of $ 1828.75.
Similarly, the north stand sold
207 140 4192
42:003:00 2:753 5 = 207(2:00) + 140(3:00) + 419(2:75) = 1986:25:
And the west stand sold
29 120 1902
42:003:00 2:753 5 = 29(2:00) + 120(3:00) + 190(2:75) = 940:50: What we just did was matrix multiplication. We multiplied a 3x3 matrix by a 3x1 matrix to get a 3x1 matrix: 2
4120 250 305
207 140 419
29 120 1903
5242:00
3:00 2:753 5 =2
41828:75
1986:25
940:53
5 { Size of matrices is important!Notice above, that we multiplied two matrices together, one was size 3x3 and the other was size 3x1. They are NOT the same size. LetAbe amxnmatrix andBbe apxqmatrix. In order to multiplyAB,the number of columns ofAmust equal thenumber of rows ofB. The schematic below will help.So, ifAbe amxnmatrix andBbe apxq, then in order to multiplyAB,nmust equalpand the
resulting size ofABismxq. { Examples:First, determine if it is possible to ndABandBAby looking at the sizes of the matrix. If so, what is the size of the resulting matrix? Find the resulting matrix.1.A=1 2
2 1 ,B=32 4 22.A=1 2
3 4 ,B=01 2 33 4 0 1
3.A=2 42 13 4 1 63 5 ,B=2 401 0
4 0 2 81 73
5 { Properties of Matrix Multiplication:LetA,B, andCbe matrices of appropriate size for matrix multiplication andcbe a scalar, then the following properties hold.
1.A(BC) = (AB)CAssociative property of multiplication
2.A(B+C) =AB+ACDistributive property
3. (A+B)C=AC+BCDistributive property
4.c(AB) = (cA)B=A(cB)
{ Commutativity:In general,AB6=BA!. Note that ifABis dened,BAmay not be dened. { Cancelation:IfAC=BC, you can NOT sayA=B. You can not simply cancel like in scalar multiplication. There are conditions onCwhich must be met in order to apply the cancelation principle. We will discuss these conditions in a later section. As an example, given A=241 2 3
0 5 4 32 135 ;B=2 446 3
5 4 4
1 0 13
5 ;C=240 0 0
0 0 0 42 335 ndACandBC. You will notice they are equal even thoughA6=B. { Properties for the Identity Matrix