Do all complex functions have orthogonal real and imaginary parts?

In summary: So the nowhere-analytic function z^ has a domain of the form (-1,1] In summary, the complex plane is a way to represent complex numbers using orthogonal functions. This means that we can find a very general Fourier series representation of any function as an infinite series of An*h(x) + infinite series of Bn*ig(x).
  • #1
cocopops12
30
0
z = h(x) + ig(x)
True or False: By the definition of the complex plane, h(x) and ig(x) will always be orthogonal.

If this was true, wouldn't that mean that we can find a 'very general' Fourier series representation of any function f(x) as an infinite series of An*h(x) + infinite series of Bn*ig(x) ?. I am aware that finding a Fourier series representation of f(x) doesn't mean that it will converge, and if it does converge, it won't necessary converge to f(x).

for example h(x) = x^2 , g(x) = ln(x)

Sorry if this is a stupid question, I'm just trying to understand some stuff...

Thanks. :smile:
 
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  • #2
No, only analytic functions are orthogonal. Most functions are not analytic. Look at the real and imaginary parts of z'(z) = z^2, as one example.
 
  • #3
I see, thank you sir!
 
  • #4
marcusl said:
No, only analytic functions are orthogonal. Most functions are not analytic. Look at the real and imaginary parts of z'(z) = z^2, as one example.

Maybe I misunderstand what you meant, but z^2 is analytic.
 
  • #5
Bacle2 said:
Maybe I misunderstand what you meant, but z^2 is analytic.
Oops, sure enough that's my mistake!:blushing:
 
  • #6
No problem, happens to all of us.
 
  • #7
marcusl said:
No, only analytic functions are orthogonal. Most functions are not analytic. Look at the real and imaginary parts of z'(z) = z^2, as one example.

[itex] z^{1/2} [/itex]
 
  • #8
LayMuon said:
[itex] z^{1/2} [/itex]

But z1/2 has a region where it is analytic; it is not entire ( it is

actually a multi-function) , but you can find a region where it is analytic.

Use, e.g., the inverse function theorem to see that there are points for which

a local inverse exists. This local inverse is analytic in a 'hood of the point.

An example of a nowhere-analytic function is z^ , the conjugate function;

with z^(x+iy):= x-iy . Then z^:=U+iV , with U(x,y)=x and V(x,y)=-y

Let's use C-R:

U_x =1 , V_y=-1 , so U_x=V_y never holds.
 
Last edited:

1. What is the definition of orthogonal real and imaginary parts in complex functions?

Orthogonal real and imaginary parts in complex functions refer to the separation of the real and imaginary components of a complex function in a way that they are perpendicular to each other. This means that the real and imaginary parts have no overlap or dependence on each other.

2. Is it true that all complex functions have orthogonal real and imaginary parts?

No, not all complex functions have orthogonal real and imaginary parts. This property only applies to certain types of complex functions, specifically those that are analytic or holomorphic.

3. What is the significance of having orthogonal real and imaginary parts in complex functions?

Having orthogonal real and imaginary parts in complex functions allows for a more efficient and simplified representation of these functions. It also helps in understanding the behavior and properties of these functions.

4. How can one determine if a complex function has orthogonal real and imaginary parts?

One way to determine if a complex function has orthogonal real and imaginary parts is by checking if it is analytic or holomorphic. Additionally, one can also check if the Cauchy-Riemann equations are satisfied, as this is a necessary condition for a complex function to have orthogonal real and imaginary parts.

5. Are there any real-world applications of complex functions with orthogonal real and imaginary parts?

Yes, there are many real-world applications of complex functions with orthogonal real and imaginary parts. These include signal processing, image compression, and electrical engineering, among others. The use of orthogonal real and imaginary parts in these applications allows for more efficient and accurate calculations and representations.

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