Calculating Fourier Transform of Unit Step Function

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The Fourier transform of the unit step function, or Heaviside step function, does not exist as a conventional function due to its infinite value at certain points. Instead, it can be represented as a distribution involving the Dirac delta function. The discussion highlights that when faced with such functions, the Laplace transform is often more applicable. Clarifications were requested on how the connection to the Dirac delta function is established and how to visualize this distribution practically. Understanding these concepts is crucial for applications in signal processing and systems analysis.
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how can I calculate the Fourier transform for unit step function:

v(t)=1 where 0=<t<+infinity

v(t)=0 otherwise

I applied the general definition relation for FT:

v(w)=integral(v(t)*e^-jwt) ; - infinity<t<+infinity

but i had v(w)=infinity due to the term infinity-displaced e^(+jwt) so that's wrong of course!

I think we could divide this function into two functions for example:

v'(t)=1/2 ; t of all values

v''(t)=1/2 ; 0=<t<+infinity
v''(t)=-1/2; -infinity<t<0

so we notice v(t)=v'(t)+v''(t)

I don't know what to do , could anyone help!

thanks!
 
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Your v(t) does not have a Fourier transform. When functions like this are encountered in practice, Laplace transform is used instead (You need to describe the application you are working on that needs this transform).
 
The Fourier transform of the Heaviside step function doesn't exist as a function. It does, however, exist as a (somewhat nasty) distribution that involves the the Dirac delta "function".

Regards,
George
 
George Jones said:
The Fourier transform of the Heaviside step function doesn't exist as a function. It does, however, exist as a (somewhat nasty) distribution that involves the the Dirac delta "function".

Regards,
George

thanks.Anyway could you clarify more, how did you deduct that Heaviside step function exists as Dirac delta function and how can we describe that distribution practically on diagram
 

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