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algebra
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linear
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vector_spaces
Linear Combination
A linear combination of the vectors
{
v
1
,
…
,
v
m
}
of vectors in a
vector space
V
is:
a
1
v
1
+
…
+
a
m
v
m
where
a
1
,
…
,
a
m
∈
𝔽
Span
The set of all linear combinations of the vectors
{
v
1
,
…
,
v
m
}
⊆
V
(where
V
is a
vector space
) called the span of
{
v
1
,
…
,
v
m
}
and we define the notation:
span
(
{
v
1
,
.
.
.
,
v
m
}
)
:
=
{
a
1
v
1
+
…
+
a
m
v
m
:
a
1
,
.
.
.
,
a
m
∈
F
}
we define
span
(
∅
)
:
=
{
0
}
Linearly Independent
A set of vectors
{
v
1
,
…
,
v
m
}
⊆
V
is said to be linearly independent if the only solution to
∑
i
=
1
m
a
i
v
i
=
0
is
∀
i
∈
{
1
,
.
.
.
,
m
}
,
a
i
=
0
. We define
∅
to be linearly independent.
Spanning Set
Suppose that
V
is a vector space, then we say that
S
is a
spanning set of
V
if
span
(
S
)
=
V
Linearly Independent iff Unique Representation
{
v
1
,
…
,
v
m
}
is linearly independent iff each vector in the set
{
v
1
,
…
,
v
m
}
has only one representation as a linear combination of
{
v
1
,
…
,
v
m
}
show proof
Linearly Dependent
{
v
1
,
…
,
v
m
}
⊆
V
is said to be linearly dependent if it is not linearly independent
Linearly Depedent iff Zero has a Non-Trivial Representation
{
v
1
,
…
,
v
m
}
⊆
V
is linearly dependent iff there exists
a
1
,
…
,
a
m
∈
F
and
i
∈
[
1
,
m
]
where
a
i
≠
0
such that
∑
i
=
1
m
a
i
v
i
=
0
show proof