This module discusses the different types of basis that leads up to the definition of an orthonormal basis. Examples are given and the useful of the orthonormal basis is discussed.
Normalized basis
Normalized Basis
a
basis
b
i where each
b
i has unit norm
You can always normalize a basis: just multiply each basis
vector by a constant, such as
1
b
i
We are given the following basis:
b
0
b
1
1
1
1
-1 Normalized with
ℓ
2 norm:
b
~
0
1
2
1
1
b
~
1
1
2
1
-1 Normalized with
ℓ
1 norm:
b
~
0
1
2
1
1
b
~
1
1
2
1
-1
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Orthogonal basis
Orthogonal Basis
a basis
b
i in which the elements are
mutually
orthogonal
i
i
j
b
i
b
j
0
Orthonormal basis
Pulling the previous two sections (definitions) together, we
arrive at the most important and useful basis type:
Orthonormal Basis
a basis that is both
normalized and
orthogonal
i
i
b
i
1
i
i
j
b
i
b
j
Notation We can shorten these two statements into one:
b
i
b
j
δ
i
j where
δ
i
j
1
i
j
0
i
j Where
δ
i
j is referred to as the Kronecker
delta function and is also often written
as
δ
i
j .
Beauty of orthonormal bases
Orthonormal bases are
very easy to deal
with! If
b
i is an orthonormal basis, we can write for any
x
It is easy to find the
α
i :
x
b
i
k
α
k
b
k
b
i
k
α
k
b
k
b
i where in the above equation we can use our knowledge of thedelta function to reduce this equation:
b
k
b
i
δ
i
k
1
i
k
0
i
k
Therefore, we can conclude the following important equation
for
x :
The
α
i 's are easy to compute (no interaction between the
b
i 's)
Slightly modified fourier series
We are given the basis
n
∞
∞
1
T
ω
0
n
t on
L
2
0
T where
T
2
ω
0 .
f
t
n
∞
∞
f
ω
0
n
t
ω
0
n
t
1
T Where we can calculate the above inner product in
L
2 as
f
ω
0
n
t
1
T
t
T
0
f
t
ω
0
n
t
1
T
t
T
0
f
t
ω
0
n
t
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Orthonormal basis expansions in a hilbert space
Let
b
i be an orthonormal basis for a Hilbert space
H . Then, for any
x
H we can write
where
α
i
x
b
i .
"Analysis": decomposing
x in term of the
b
i
"Synthesis": building
x up out of a weighted combination of the
b
i