Annex
A
(normative)
Mathematical foundations
This annex identifies the concepts from mathematics used in this International Standard and specifies the notation used for those concepts. No proofs are presented. A reader of this International Standard is assumed to be familiar with mathematics including set theory, linear algebra, and the calculus of several real variables as presented in reference works such as the Encyclopedic Dictionary of Mathematics [EDM].
An ordered set of n real numbers a where n is a natural number is
called an n-tuple of real numbers and shall be denoted by 
The
set of all n-tuples of real numbers is denoted by Rn. Rn is an n-dimensional vector space.
The canonical basis for Rn is defined as:
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The elements of Rn may be called points or vectors. The latter term is used in the context of directions or vector space operations.
The zero vector 
is
denoted by 0.
Definitions A.2(a) through A.2(j) apply to any vectors
and 
in Rn:
a) The inner product or dot-product of two vectors x and y is defined as:
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b)
Two vectors x
and y are called orthogonal if 
= 0.
c) If n ≥ 2, two vectors x and y are called perpendicular if and only if they are orthogonal.
NOTE
1 If n ≥ 2, 
where
α is the angle between x
and y.
d) x is called orthogonal to a set of vectors if x is orthogonal to each vector that is a member of the set.
e) The norm of x is defined as
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Note 2 The norm of x represents the length of the vector x. Only the zero vector 0 has norm zero.
f)
x is called normalized if
.
g) A set of two or more normalized and pair-wise orthogonal vectors is called an orthonormal set of vectors.
Example The canonical basis is an example of an orthonormal set of vectors.
h) The Euclidean metric d is defined by
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d(x, y) = ||x – y||. |
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i) The value of d(x, y) is called the Euclidean distance between x and y.
j) The cross product of two vectors x and y in R3 is defined as the vector:
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Note 3 The vector x × y is orthogonal to both x and y, and
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where α is the angle between vectors x and y.
A.3 The point set topology of Rn
Given a point p in Rn and a real value ε > 0, the set {q in Rn | d(p, q) < ε } is called the ε-neighbourhood of p.
Given a set D
Rn and a point p, the
following terms are defined:
a) p is an interior point of D if at least one ε-neighbourhood of p is a subset of D.
b) The interior of a set D is the set of all points that are interior points of D.
NOTE 1 The interior of a set may be empty.
c) D is open if each point of D is an interior point of D. Consequently, D is open if it is equal to its interior.
d) p is a closure point of D if every ε-neighbourhood of p has a non-empty intersection with D.
Note 2 Every member of D is a closure point of D.
e) The closure of a set D is the set of all points that are closure points of D.
f) D is a closed set if it is equal to the closure set of D.
g) A set D is replete if all points in D belong to the closure of the interior of D.
Note 3 Every open set is replete. The union of an open set with any or all of its closure points forms a replete set. In particular, the closure of an open set is replete.
EXAMPLE 1 In R2 {(x, y) | -π < x < π, -π/2 < y < π/2} is open and therefore replete.
EXAMPLE 2 {(x, y) | -π < x ≤ π, -π/2 < y < π/2} is replete.
EXAMPLE 3 {(x, y) | -π ≤ x ≤ π, -π/2 ≤ y ≤ π/2} is closed and replete.
Many concepts traditionally defined on open sets can be extended by continuity to replete sets. In particular, if f is a continuous function defined on a replete set D, and if f is continuously differentiable on the interior of D, the derivative of f shall be extended by continuity to all of D.
NOTE 4 The usual definition of the derivative of a function is restricted to open sets.
A real-valued function f defined on a replete domain in Rn is called smooth if its first derivative exists and is continuous at each point in its domain.
The gradient of f is the vector of first order partial derivatives
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Definitions A.4(a) through A.4(g) apply to any vector-valued function F defined on a replete domain D in Rn with range in Rm
a)
The ith-component
function of a vector-valued function F is
the real-valued function fi defined by fi = ei •F
where ei is the
ith canonical basis vector, 
.
In this case:
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F(v)
= (f1(v),
f2(v),
f3(v),
…, fn(v)) for v = (v1, v2, v3, …,vn) in D, |
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b) F is called smooth if each component function fi is smooth, .
c) The first derivative of a smooth vector-valued function F, denoted dF, evaluated at a point in the domain is the n × m matrix of partial derivatives evaluated at the point:
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d) The Jacobian matrix of F at the point v is the matrix of the first derivative of F.
NOTE 1 The rows of the Jacobian matrix are the gradients of the component functions of F.
e) In the case m = n, the Jacobian matrix is square and its determinant is called the Jacobian determinant.
f) In the case m = n, F is called orientation preserving if its Jacobian determinant is strictly positive for all points in D.
g) A vector-valued function F defined on Rn is linear if:
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F(ax + y) = aF(x) + F(y) for all real scalars a and vectors x and y in Rn. |
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NOTE 2 All linear functions are smooth.
A vector-valued function E
defined on Rn is affine if F, defined by
, is
a linear function. All affine functions on Rn are smooth.
A function may be alternatively called an operator especially when attention is focused on how the function maps a set of points in its domain onto a corresponding set of points in its range.
EXAMPLE The localization operators (see 5.7)
If F
and G are two vector valued functions and the range of G is contained in the domain of F, then
, the composition of F with G, is the
function defined by 
has the same domain as G,
and the range of is
contained in the range of F.
Functional composition also applies to
scalar-valued functions f and g, If the range of g is contained
in the domain of f, then 
the composition of f with g, is the function defined by 
A.6.1 Implicit definition
A smooth surface in R3 is implicitly specified by a real-valued smooth function f defined on R3 as the set S of all points (x, y, z) in R3 satisfying:
a) f(x, y, z) = 0 and
b) grad( f )(x, y, z) ≠ 0.
In this case, f is called a surface generating function for the surface S.
EXAMPLE 1 If n ≠ 0 and p
are vectors in R3 and f(v) = n•(v – p), then f is smooth and 
The plane which is
perpendicular to n and contains p is the smooth surface
implicitly defined by the surface generating function f.
Special cases:
When n = (1, 0, 0) and p = 0, the yz-plane is implicitly defined.
When n = (0, 1, 0) and p = 0, the xz-plane is implicitly defined.
When n = (0, 0, 1) and p = 0, the xy-plane is implicitly defined.
The surface normal n at a point p = (x, y, z) on the surface implicitly specified by a surface generating function f is defined as:
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NOTE -n is also a surface normal to S at p. The surface generating function f determines the surface normal direction: n or -n.
The tangent plane to a surface at a point p = (x, y, z) on the surface S implicitly defined by a surface generating function f is the plane which is the smooth surface implicitly defined by h(v) = n • (v–p) where n is the surface normal to S at p.
EXAMPLE 2 If a and b are positive non-zero scalars, define
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Then f is smooth and
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is never (0, 0, 0) on the surface implicitly specified by the set satisfying f = 0.
A.6.2 Ellipsoid surfaces
If a and b are positive non-zero scalars, the smooth function:
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is a surface generating function for a ellipsoid of revolution smooth surface S.
When b ≤ a, the surface is called an oblate ellipsoid. In this case a is called the major semi-axis29 of the oblate ellipsoid and b is called the minor semi-axis of the oblate ellipsoid.
The flattening of an oblate ellipsoid is defined as f = (a - b)/a.
The eccentricity of an oblate ellipsoid is defined as 
.
The second
eccentricity of an oblate ellipsoid is defined as 
.
When b = a, the oblate ellipsoid may be called a sphere of radius r = b = a.
When a < b, the surface is called a prolate ellipsoid. In this case, a is called the minor semi-axis of the prolate ellipsoid and b is called the major semi-axis of the prolate ellipsoid.
NOTE
1 A sphere of radius r is also implicitly
defined by the surface generating function 
NOTE 2 The term spheroid is often used to denote an oblate ellipsoid with an eccentricity close to zero (“almost spherical”).
A smooth curve in Rn is parametrically specified by a smooth one-to-one Rn valued function F(t) defined on a replete interval I in R such that ||dF(t)|| ≠ 0 for any t in I.
EXAMPLE 1 If p and n are vectors in Rn such that n ≠ 0 and L(t) = p + t n, -∞ < t < +∞, then L is smooth and ||dL(t)|| = ||n|| > 0. The line which is parallel to n and which contains p is a smooth curve parametrically specified by L.
EXAMPLE 2 If a and b are positive non-zero scalars and b ≤ a, define
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F(t) = (a cos(t), b sin(t)) for all t in the interval -p < t ≤ p. |
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Then F is smooth and ||dF(t)|| ≥ b > 0 for all t in the interval and therefore parametrically specifies a smooth curve in R2.
An ellipse in R2 with major semi-axis a and minor semi-axis b, 0 < b ≤ a, is parametrically specified by:
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F(t) = (a cos(t), b sin(t)), for all t in the interval -π < t ≤ π. |
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A.7.1.2 Tangent to a smooth curve
If C(t) parametrically specifies a smooth curve C passing through a point p = C(tp), the tangent vector to C at p shall be defined as:
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where dC(tp) = (dC1/dt, dC2/dt, …, dCn/dt) is the first derivative of C evaluated at tp.
NOTE -t is also a tangent vector to C at p. The parameterization function C(t) determines the tangent vector direction: t or -t.
A locus of points is a directed curve if it is the range of a smooth curve.
The tangent line to the curve C at p is a smooth curve parametrically specified by T(s) = p + s t, -∞ < s < +∞, where t is a tangent vector to C at p. See Figure A.1.
Figure A.1 — Tangent to a curve
If two parametrically specified smooth curves C1 and C2 intersect at a point p then the angle at p from C1 to