Orthogonality of 2 complex exponentials

  • #1
Nana113
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For 2 complex functions, to find the orthogonality, one of the function has to be in complex conjugate? Because in the lecture note, the first formula is without complex conjugate, so I’m a bit confused

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  • #2
The inner product of two complex things always involves the complex conjugate of one of the things. In this case:$$\langle u, v \rangle = \int_a^b u(x)^*v(x) \ dx$$There are loads of hits on Goggle if you search for "complex inner product".
 
  • #3
PeroK said:
The inner product of two complex things always involves the complex conjugate of one of the things. In this case:$$\langle u, v \rangle = \int_a^b u(x)^*v(x) \ dx$$There are loads of hits on Goggle if you search for "complex inner product".
so this condition always applies and the integral always equates to 0 when asking for orthogonality?
 
  • #4
Nana113 said:
so this condition always applies and the integral always equates to 0 when asking for orthogonality?
That's the definition of orthogonality. It's a generalization of the concept of orthogonality for 2D or 3D vectors. Vectors (or functions) are orthogonal if $$\langle u, v \rangle = 0$$In this case that means that two functions are orthogonal if$$\int_a^b u(x)^*v(x) \ dx = 0$$
 
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  • #5
Just to add a couple of things.

PeroK said:
The inner product of two complex things always involves the complex conjugate of one of the things. In this case:$$\langle u, v \rangle = \int_a^b u(x)^*v(x) \ dx$$There are loads of hits on Goggle if you search for "complex inner product".
The reason for this being that the inner product is supposed to satisfy ##\langle v,u\rangle = \langle u,v\rangle^*##, resulting in linearity in one argument and anti-linearity in the other.

PeroK said:
In this case that means that two functions are orthogonal if$$\int_a^b u(x)^*v(x) \ dx = 0$$
It should however be noted that an inner product on a function space will often come with an additional weight function. In this case it does not, but it is good to be aware.
 
  • #6
Orodruin said:
Just to add a couple of things.The reason for this being that the inner product is supposed to satisfy ##\langle v,u\rangle = \langle u,v\rangle^*##, resulting in linearity in one argument and anti-linearity in the other.
It also, i'd say the main point, makes it positive definite. ##\langle u, u \rangle > 0## for non zero vectors.
 
  • #7
PeroK said:
The inner product of two complex things always involves the complex conjugate of one of the things. In this case:$$\langle u, v \rangle = \int_a^b u(x)^*v(x) \ dx$$There are loads of hits on Goggle if you search for "complex inner product".

An inner product on a complex vector space is by definition linear in its first argument and Hermitian (see eg. here), so that [tex]\langle \alpha u, v \rangle = \alpha \langle u, v \rangle[/tex] but [tex]\langle u, \alpha v \rangle = (\langle \alpha v, u \rangle)^{*} = \alpha^{*}\langle u, v \rangle.[/tex] Hence we must have [tex]\langle u, v \rangle = \int_a^b u(x)v^{*}(x)\,dx.[/tex]
 
  • #8
pasmith said:
An inner product on a complex vector space is by definition linear in its first argument and Hermitian (see eg. here), so that [tex]\langle \alpha u, v \rangle = \alpha \langle u, v \rangle[/tex] but [tex]\langle u, \alpha v \rangle = (\langle \alpha v, u \rangle)^{*} = \alpha^{*}\langle u, v \rangle.[/tex] Hence we must have [tex]\langle u, v \rangle = \int_a^b u(x)v^{*}(x)\,dx.[/tex]
Yeah, but that messes up Dirac notation!
 
  • #9
pasmith said:
An inner product on a complex vector space is by definition linear in its first argument
Note: This is the typical definition among mathematicians. Among phycisists, the typical convention is that the linearity is in the second argument. One needs to be careful to ensure oneself which convention a particular source uses.
 
  • #10
PeroK said:
Yeah, but that messes up Dirac notation!
Because Dirac notation is typically used by physicists. See above.
 
  • #11
so my working out of the question attached is correct?
 
  • #12
Nana113 said:
so my working out of the question attached is correct?
Looks fine to me.
 

1. What is the definition of orthogonality of 2 complex exponentials?

Orthogonality of 2 complex exponentials refers to the property where the inner product of two complex exponential functions is equal to zero. Mathematically, this can be represented as ∫(e^(jω1t))(e^(-jω2t)) dt = 0 for ω1 ≠ ω2.

2. How is the orthogonality of 2 complex exponentials useful in signal processing?

The orthogonality of 2 complex exponentials is fundamental in signal processing as it allows for the decomposition of signals into simpler components. By leveraging this property, signals can be efficiently analyzed and processed using techniques such as Fourier analysis and signal modulation.

3. Can orthogonality of 2 complex exponentials be extended to more than 2 functions?

Yes, the concept of orthogonality of complex exponentials can be extended to more than 2 functions. In general, a set of complex exponentials is said to be orthogonal if the inner product between any two distinct functions in the set is zero. This property is widely used in various mathematical and engineering applications.

4. How does orthogonality of complex exponentials relate to the Fourier transform?

The orthogonality of complex exponentials plays a crucial role in the theory of Fourier transform. In particular, the Fourier transform decomposes a signal into its frequency components by representing the signal as a linear combination of complex exponential functions. The orthogonality property ensures that the frequency components are isolated and can be analyzed independently.

5. Are there any practical implications of violating the orthogonality of complex exponentials?

Violating the orthogonality of complex exponentials can lead to signal distortion and interference in signal processing applications. When the orthogonality property is not satisfied, it becomes challenging to accurately analyze and manipulate signals. Therefore, ensuring the orthogonality of complex exponentials is crucial for maintaining the integrity of signal processing systems.

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