Fourier Transform of integral of a signal

AI Thread Summary
The discussion focuses on the continuous time Fourier Transform of the integral of a signal, specifically how to express it in terms of frequency f instead of angular frequency ω. The transformation shows that the integral of the signal leads to a term involving the delta function, where the coefficient changes from π to 1/2 when converting to frequency f. This is explained by the relationship between the delta functions, where δ(ω) is equivalent to δ(2πf) scaled by 1/(2π). The participants clarify the mathematical reasoning behind these transformations and the implications for signal analysis. Understanding these relationships is crucial for accurate signal processing in the frequency domain.
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Hi. I have a question regarding the continuous time Fourier Transform of an input signal:

x(t) \rightarrow X(j\omega)

then

\int_{-\infty}^{t}x(\tau)d\tau \rightarrow \frac{X(j\omega)}{j\omega} + \pi X(0)\delta(\omega)

but if I want to write it in terms of f = \frac{\omega}{2\pi}, should it be:

\int_{-\infty}^{t}x(\tau)d\tau \rightarrow \frac{X(j\omega)}{j\omega} + \frac{1}{2}X(0)\delta(f)

How does the \pi get replaced by \frac{1}{2} here?
 
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How does the \pi get replaced by \frac{1}{2} here?[/QUOTE]

For a>0, what does \delta (ax ) equal? Why?
 
Oh ok, so

\delta(\omega) = \delta(2\pi f) = \frac{1}{2\pi}\delta(f)

Thanks :cool:
 
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