You may have run across inner products, also
called dot products, on
Rn
n
before in some of your math or science courses. If
not, we define the inner product as follows, given we have some
x∈Rn
x
n
and
y∈Rn
y
n
- Definition 1: inner product
The inner product is defined mathematically as:
〈x,y〉=yTx=(
y
0
y
1
…
y
n
−
1
)
x
0
x
1
⋮
x
n
−
1
=∑
i
=0n−1
x
i
y
i
x
y
y
x
y
0
y
1
…
y
n
−
1
x
0
x
1
⋮
x
n
−
1
i
n
1
0
x
i
y
i
(1)
If we have
x∈R2
x
2
and
y∈R2
y
2
, then we can write the inner product as
〈x,y〉=∥x∥∥y∥cosθ
x
y
x
y
θ
(2)
where
θθ is the angle
between
xx and
yy.
Geometrically, the inner product tells us about the
strength of xx in the direction of
yy.
For example, if
∥x∥=1
x
1
, then
〈x,y〉=∥y∥cosθ
x
y
y
θ
The following characteristics are revealed by the inner
product:
-
〈x,y〉
x
y
measures the length of the
projection of yy onto
xx.
-
〈x,y〉
x
y
is maximum (for given
∥x∥
x
,
∥y∥
y
)
when xx
and yy are
in the same direction (
(θ=0)⇒(cosθ=1)
θ
0
θ
1
).
-
〈x,y〉
x
y
is zero when
(cosθ=0)⇒(θ=90°)
θ
0
θ
90°
, i.e. xx and yy are
orthogonal.
In general, an inner product on a complex vector space is
just a function (taking two vectors and returning a complex
number) that satisfies certain rules:
-
Conjugate Symmetry:
〈x,y〉=〈x,y〉¯
x
y
x
y
-
Scaling:
〈αx,y〉=α〈(x,y)〉
α
x
y
α
x
y
-
Additivity:
〈x+y,z〉=〈x,z〉+〈y,z〉
x
y
z
x
z
y
z
-
"Positivity":
∀
x
,x≠0:〈x,x〉>0
x
x
0
x
x
0
- Definition 2: orthogonal
We say that xx
and yy are
orthogonal if:
〈x,y〉=0
x
y
0