Orthonormality of Fourier functions

In summary, the coefficients in a Fourier expansion are typically expected to be the projections of the function onto the different Fourier functions, which should form an orthonormal basis. However, the conventional formula for the coefficients includes a factor of 2 for the sines and cosines, and these functions do not form an orthonormal set. This can be resolved by redefining the inner product to be 1/pi times the integral of the product of two functions over the interval [-pi,pi]. In this case, the sines and cosines will be orthonormal to each other. The use of the exponential form of the Fourier series also yields an orthonormal set of functions, but this may be due to the 1
  • #1
NanakiXIII
392
0
Looking at a Fourier expansion,

[tex]f(x) = a_0 + a_1 \cos{x} + b_1 \sin{x} + a_2 \cos{2 x} + b_2 \sin{2 x} + ...[/tex],

I would expect the coefficients to be the projections of [tex]f(x)[/tex] on the different Fourier functions, which should form an orthonormal basis. This doesn't seem to be the case, though. The formulae for the coefficients say

[tex]a_0 = \frac{1}{2 \pi} \int_{-\pi}^{\pi} f(x) 1 dx[/tex];

[tex]a_n = \frac{1}{2 \pi} \int_{-\pi}^{\pi} f(x) 2 \cos{n x} dx[/tex];

[tex]b_n = \frac{1}{2 \pi} \int_{-\pi}^{\pi} f(x) 2 \sin{n x} dx[/tex].

Now, assuming that the inner product is defined as

[tex]<f,g> = \frac{1}{2 \pi} \int_{-\pi}^{\pi} f(x) g(x) dx[/tex],

these coefficients are not simply the projections, since the sines and cosines get a factor two. Further more, these sines and cosines do not form an orthonormal set. So what exactly is going on? Are my assumptions about the nature of the coefficients or about the expected orthonormality of the functions wrong?

I also noticed that if you use the exponential form of the Fourier series, all the functions are perfectly orthonormal and the coefficients are indeed the projections on these functions. Perhaps something happens when changing from exponential form to sine and cosine form?
 
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  • #2
So Redefine the inner product to be:

[tex]<f,g>=\frac{1}{\pi}\int^{\pi}_{-\pi}f(x)g(x)dx[/tex]

And then the sines and cosines will be orthonormal to each other ( the constant function will need refactoring, it's the only function that doesn't blend nicely into the set).

Convention gives the next sum:

[tex]f(x) -> \frac{a_{0}}{2}+\sum^{\infty}_{n=1}a_{n}cos(nx)+b_{n}sin(nx)[/tex]

Where

[tex]a_{0}=\frac{1}{\pi}\int^{\pi}_{-\pi}f(x)dx[/tex]
[tex]a_{n}=\frac{1}{\pi}\int^{\pi}_{-\pi}f(x)cos(nx)dx[/tex]
[tex]b_{n}=\frac{1}{\pi}\int^{\pi}_{-\pi}f(x)sin(nx)dx[/tex]I must add that dealing with orthonormallity is quite artificial. You can always normalize every function given an inner product (assuming of course, it is of the integral form). The center of the Fourier Series (and Sturm-Liouville comes in too) Theorem is the orthogonality.

P.S. About your last paragraph regarding the exponential basis. Yes, there is this 1/2 factor when considering Euler's Identities:

[tex]sin(x)=\frac{1}{2i}(e^{ix}-e^{-ix})[/tex]
[tex]cos(x)=\frac{1}{2}(e^{ix}+e^{-ix})[/tex]

Perhaps this is what causes the orthonormality of the exponentials with the 1/(2pi) inner product.
 
  • #3
I hadn't though of it. You can of course absorb a factor 2 into [tex]a_0[/tex] to make your functions orthonormal. Thanks.
 

1. What is the concept of orthonormality in Fourier functions?

The concept of orthonormality in Fourier functions refers to the property of two functions being orthogonal (perpendicular) and normalized (having a magnitude of 1) to each other. This means that the inner product (or integral) of the two functions is equal to 0, and their individual magnitudes are equal to 1. In other words, orthonormal Fourier functions are a set of functions that are mutually orthogonal and have a magnitude of 1, making them useful for representing any periodic function.

2. How is orthonormality used in Fourier series?

In Fourier series, orthonormality is used to decompose a periodic function into a sum of simpler functions, known as Fourier basis functions. The orthonormality of these functions ensures that the coefficients in the series can be easily calculated using the inner product of the function and each basis function. This allows for efficient representation and manipulation of periodic functions in various applications, such as signal processing and data compression.

3. What are the benefits of using orthonormal Fourier functions?

Orthonormal Fourier functions have several benefits, including their ability to efficiently represent and manipulate periodic functions. They also have the property of being orthogonal and normalized, which simplifies the calculation of Fourier coefficients and helps to reduce errors. Additionally, orthonormal Fourier functions have a wide range of applications, making them a valuable tool in various scientific fields.

4. Can any function be represented as a series of orthonormal Fourier functions?

Yes, any periodic function can be represented as a series of orthonormal Fourier functions. This is known as the Fourier series representation and is based on the fundamental theorem of Fourier series, which states that any periodic function can be expressed as a sum of orthonormal functions with specific coefficients. However, the convergence of the Fourier series representation may vary depending on the function being represented.

5. How is orthonormality related to the Fourier transform?

The Fourier transform is a mathematical operation that decomposes a function into its frequency components. Orthonormality is related to the Fourier transform because the Fourier transform of an orthonormal function is also orthonormal. This means that the Fourier transform preserves the orthonormality property, making it a useful tool for analyzing and manipulating signals and data represented in the frequency domain.

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