2. Scalar Quantity
(mass, speed, voltage, current and power)
1- Real number (one variable)
2- Complex number (two variables)
Vector Algebra
(velocity, electric field and magnetic field)
Magnitude & direction
1- Cartesian (rectangular)
2- Cylindrical
3- Spherical
Specified by one of the following
coordinates best applied to application:
Page 101
3. Conventions
• Vector quantities denoted as or v
• We will use column format vectors:
• Each vector is defined with respect to a set of
basis vectors (which define a co-ordinate
system).
v
[ ] [ ]( )T
vvvvvv
v
v
v
321321
3
2
1
=≠
=v
5. Vectors
• Vectors represent directions
– points represent positions
• Both are meaningless
without reference to a
coordinate system
– vectors require a set of basis
vectors
– points require an origin and a
vector space
=
=
y
x
y
x
v
v
v
v
Pv
both vectors equal
6. Co-ordinate Systems
• Until now you have probably used a Cartesian
basis:
– basis vectors are mutually orthogonal and
unit length
– basis vectors named x, y and z
• We need to define the relationship between the
3 vectors.
8. Vector Magnitude
• The magnitude or norm of a vector of
dimension n is given by the standard
Euclidean distance metric:
• For example:
• Vectors of length 1(unit) are normal vectors.
222
21 n
vvv +++= v
11131
1
3
1
222
=++=
9. Normal Vectors
• When we wish to describe direction we
use normalized vectors.
• We often need to normalize a vector:
v
v
v
v
222
21
1
n
vvv +++
==′
14. Problem 3-1
• Vector starts at point (1,-1,-2) and ends
at point (2,-1,0). Find a unit vector in the
direction of .
A
A
y
x
z
( ) ( )( ) ( )( )20ˆ11ˆ12ˆ −−+−−−+−= zyxA
15. Problem 3-1
( ) ( )( ) ( )( )20ˆ11ˆ12ˆ −−+−−−+−= zyxA
y
x
z
( )2,1,11 −−P
( )0,1,22 −P
A
17. Vector MultiplicationVector Multiplication
1- Simple Product
2- Scalar or Dot Product
3- Vector or Cross Product
1- Simple Product
)(ˆ)(ˆ)(ˆˆ zyx kAzkAykAxkAaAkB ++===
Scalar or Dot Product
ABABBA Θ=⋅ cos
Page 104
18. Vector Multiplication by a Scalar
• Each vector has an associated length
• Multiplication by a scalar scales the vectors
length appropriately (but does not affect
direction):
19. Dot Product
• Dot product (inner product) is defined as:
[ ] 332211
3
2
1
321 vuvuvu
v
v
v
uuuT
++=
==⋅ vuvu
∑=⋅
i
iivuvu
θcosvuvu =⋅
20. Dot Product
• Note:
• Therefore we can redefine magnitude in terms
of the dot-product operator:
• Dot product operator is commutative &
distributive.
22
3
2
2
2
1 uuu =++=⋅ uuu
uuu ⋅=
21. Problem 3.2
• Given vectors:
– show that is perpendicular to both
and .
A
B
C
zyxA ˆ3ˆ2ˆ +−=
3ˆˆ2ˆ zyxB +−=
2ˆ2ˆ4ˆ zyxC −+=
27. Problem 3.3
• In the Cartesian coordinate system, the
three corners of a triangle are P1(0,2,2),
P2(2,-2,2), and P3(1,1,-2). Find the area
of the triangle.
43. Let
4ˆ2ˆ21 yxB −== PP
and
4ˆˆˆ31 zyxC −−== PP
→
→
represent two sides of the triangle.
Since the magnitude of the cross product is the
area of the parallelogram, half of this magnitude
is the area of the triangle.
47. y
x
z
( )
( )
4.63,90,24.2
107.1,57.1,51
≈
radradP
φ
r
5014222
=++=++= zyxr
rad
x
y
107.1
1
2
tantan 11
=
=
= −−
φ
0=h
rad
z
yx
57.1
0
5
tantan 1
22
1
=
=
+
= −−
θ
Convert the coordinates of
P1(1,2,0) from the
Cartesian to the Spherical
coordinates.
48. y
x
z
Convert the coordinates of P3(1,1,2) from the Cartesian to
the Cylindrical and Spherical coordinates.
( )2,1,11P
21122
=+=+= yxr
2=h
rad
x
785.0
1
1
tan
1
tan 11
=
=
= −−
φ
49. y
x
z
Convert the coordinates of P3(1,1,2) from the Cartesian to
the Cylindrical coordinates.
2,
4
,23 radP
π
21122
=+=+= yxr
2=h
rad
x
785.0
1
1
tan
1
tan 11
=
=
= −−
φ
50. y
x
z
Convert the coordinates of P3(1,1,2) from the Cartesian to
the Spherical coordinates.
( )
45,3.35,45.23P
6211 222222
=++=++= zyxr
rad616.0
2
2
tan
2
11
tan 1
22
1
=
=
+
= −−
θ
( ) rad
4
1tan
1
1
tan 11 π
φ ==
= −−
Hinweis der Redaktion
Vectors are used extensively in computer graphics, we use them to represent the positions of points in a world-coordinate dataset, the orientation of surfaces in space, the behaviiours of light interactin with sold and transparent objects.
A vector is an n-tuple of real numbers, where n is 2 for 2D space, and 3 for 3D space etc, vectors can be denoted by italices, in bold face, or with an arrow above them to indicate direction. Vectors are amenable to two operations, addition of vectors and multiplication of vectors by real numbers – called SCALAR MULTIPLICATION.
It is important to make the distinction between vectors and points. While we can think of a point as being defined by a vector that it drawn to it, this representation requires us to specify WHERE the the vector is drawn from, define what we usually call the origin. - it is best not to confuse the nature of vectors and points, but to treat them as separate entities.
Addition is defined component wise, as is scalar multipication, vectors are written vertically
Do EXAMPLE,
give them an EXAMPLE
WE can define addition of vectors by the well known parallelogram rule – to add the vectors u and v, we take an arrow from the origin to u,, translate it such that its base is at point v and define v + u as the new endpoint of the arrow, if we also draw the arrow from the origin to v, and do the corresponding process we get a parallelogram.
Addition is defined component wise, as is scalar multipication, vectors are written vertically
Do EXAMPLE,
give them an EXAMPLE
WE can define addition of vectors by the well known parallelogram rule – to add the vectors u and v, we take an arrow from the origin to u,, translate it such that its base is at point v and define v + u as the new endpoint of the arrow, if we also draw the arrow from the origin to v, and do the corresponding process we get a parallelogram.
Draw an arrow from origin to the point and stretch it by the factor of the scalar, holding the end at the origin fixed, alpha v is then defined as the endpoint of the resulting arrow.
Given 2 n-dimensional vectors we define their x1y1+x2y2...xnyn. the dot product is generally denoted u.v
Given 2 n-dimensional vectors we define their x1y1+x2y2...xnyn. the dot product is generally denoted u.v