Theorem: derivative of the Fourier transform

In summary, the proof of the theorem states that for all real x, there exists a function tx() such that x(t) is a summable majorant for tx(), and the average rate of change of x is equal to the sum of the squares of the differences between tx() and x(t).
  • #1
eliotsbowe
35
0
Hello, I'm dealing with the proof of the theorem below:

[itex]x(t) \in L^1(\mathbb{R}), tx(t) \in L^1(\mathbb{R}) \Rightarrow \mathfrak{F}[x(t)] \in C^1(\mathbb{R})[/itex]and[itex]\frac{\mathrm{d} }{\mathrm{d} \omega}\mathfrak{F}[x(t)](\omega) = \mathfrak{F}[-jtx(t)][/itex]I'm going to write down an interesting proof that I found, which is based on Lebesgue's dominated convergence theorem:

Let [itex]X(\omega)[/itex] be the Fourier transform of x(t). Let's consider average rate of change of X:
[itex]\frac{X(\omega + \Delta \omega) - X ( \omega)}{\Delta \omega} = \int_{-\infty}^{+\infty}\frac{x(t) e^{-j(\omega + \Delta \omega)t}}{\Delta \omega}dt - \int_{-\infty}^{+\infty}\frac{x(t) e^{-j(\omega)t}}{\Delta \omega}dt = \int_{-\infty}^{+\infty}\frac{x(t) e^{-j(\omega + \Delta \omega)t}}{\Delta \omega} - \frac{x(t) e^{-j(\omega)t}}{\Delta \omega}dt =[/itex]

[itex]=\int_{-\infty}^{+\infty} x(t) e^{-j \omega t} [ \frac{e^{-j \Delta \omega t} - 1} { \Delta \omega }] dt[/itex]

Now there's a step I don't understand:

[itex]\forall \Delta \omega[/itex] we have:
[itex]|x(t) e^{-j\omega t} \frac{e^{-j \Delta \omega t} - 1}{\Delta \omega}|=|tx(t) \frac{e^{-j \Delta \omega t} - 1}{-jt\Delta \omega }| = |tx(t)||\frac{e^{-j \Delta \omega t} - 1}{-jt\Delta \omega }| \leq |tx(t)|[/itex]

(The thesis follows by noticing that tx(t) is a summable majorant for the integrandus, thus we can pass the [itex]\Delta \omega \to 0[/itex] limit inside the integral).

In particular, I don't understand the disequation:
[itex]|\frac{e^{-j \Delta \omega t} - 1}{-jt\Delta \omega }| \leq 1[/itex] , for any [itex]\Delta \omega[/itex]
What am I missing?

Thanks in advance.
 
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  • #2
I use i not j. The following is for all real x.

|eix - 1|=|eix/2 - e-ix/2|=2|sin(x/2)|≤|x|
 
  • #3
mathman said:
I use i not j. The following is for all real x.

|eix - 1|=|eix/2 - e-ix/2|=2|sin(x/2)|≤|x|

Thanks a lot!
 

1. What is the Fourier transform?

The Fourier transform is a mathematical operation that decomposes a function into its constituent frequencies. It converts a time domain function into a frequency domain function, providing a representation of the function in terms of sinusoidal components.

2. What is the derivative of the Fourier transform?

The derivative of the Fourier transform is a mathematical operation that calculates the rate of change of the Fourier transform with respect to the variable being transformed. It can also be interpreted as the Fourier transform of the derivative of the original function.

3. How is the derivative of the Fourier transform calculated?

The derivative of the Fourier transform is calculated using the differentiation property of the transform. This property states that the Fourier transform of the derivative of a function is equal to the derivative of the Fourier transform of the function.

4. What is the significance of the derivative of the Fourier transform in signal processing?

The derivative of the Fourier transform has many applications in signal processing, such as in the analysis of time-varying signals and the identification of system properties. It can also be used to enhance the resolution of spectral analysis and to filter out noise from a signal.

5. Are there any limitations or assumptions when using the derivative of the Fourier transform?

Like any mathematical operation, there are limitations and assumptions when using the derivative of the Fourier transform. Some of these include the requirement of the function being differentiable and the assumption that the function and its derivative have finite Fourier transforms. Additionally, care must be taken when interpreting the results, as the derivative of the Fourier transform can magnify high-frequency noise in the original signal.

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