Fourier transformation and test function -- Question in the derivation

In summary: Finally, to answer your question about how they "drag out" $f$, we can see that it comes from the exponential term in the FT. When we take the derivative of this term, we get a factor of $f$ in front of the integral. This is where the $f$ comes from.In summary, the proof of the derivative rule of FT involves using the linearity property of the FT and manipulating the variables in the integral to arrive at the final result. It is a straightforward application of calculus and understanding the properties of the FT.
  • #1
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How does it work? (The derivative rules of FT)
We look at $$F[x(t)]=\hat{x}(f)$$
$$\mathcal{l} \text{ is a distribution, with}\tilde{x}=tx(t)$$
$$\mathcal{F}[Dl(x)]=\mathcal{F}l'(x)=2\pi il(\mathcal{F}\tilde{x})=2\pi i \mathcal{F}l(\tilde{x})$$
Till here I fully understand. But next step:
$$=2\pi i fFl(x)$$
How do they drag out f and make x~=tx(t) to x?

**Well, of course this is just a proof of derivative rule of FT, which is not hard
$$\mathcal{F}x'=2\pi i f \hat{x}$$
 
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  • #2


The first step in understanding this proof is to understand the definition of the Fourier Transform (FT) and its properties. The FT is a mathematical operation that decomposes a function into its constituent frequencies. It is defined as follows:

$$\hat{f}(\xi) = \int_{-\infty}^{\infty} f(x)e^{-2\pi i\xi x} dx$$

where $f(x)$ is the function being transformed and $\xi$ is the frequency variable.

One of the properties of the FT is that it is linear, which means that it follows the rules of linear algebra. This means that if we have two functions $f(x)$ and $g(x)$, and we take the FT of their sum, it is equal to the sum of their individual FTs. Mathematically, this can be written as:

$$\mathcal{F}[f(x)+g(x)] = \hat{f}(\xi) + \hat{g}(\xi)$$

Now, let's look at the first step in the proof that you mentioned:

$$\mathcal{F}[Dl(x)]=\mathcal{F}l'(x)=2\pi il(\mathcal{F}\tilde{x})=2\pi i \mathcal{F}l(\tilde{x})$$

In this step, we are using the linearity property of the FT. We are taking the FT of the derivative of a function $l(x)$, which is denoted as $Dl(x)$. This is equivalent to taking the derivative of the FT of $l(x)$, which we have denoted as $l'(x)$. This is a standard rule in calculus.

Next, we are using the fact that $\tilde{x}=tx(t)$. This means that we are multiplying the original function $x(t)$ by the variable $t$. In other words, we are stretching or compressing the function in the time domain. This is a common technique in signal processing.

Now, let's look at the next step:

$$=2\pi i fFl(x)$$

In this step, we are simply using the definition of the FT and plugging in the value of $\tilde{x}$, which we know is equal to $tx(t)$. This gives us:

$$=2\pi i \int_{-\infty}^{\infty
 

1. What is a Fourier transformation?

A Fourier transformation is a mathematical operation that decomposes a function into its individual frequency components. It converts a function from its original domain (usually time or space) to its corresponding frequency domain.

2. What is the purpose of a Fourier transformation?

The purpose of a Fourier transformation is to simplify the analysis of complex functions and phenomena by breaking them down into simpler components. It is commonly used in signal processing, image processing, and other fields of science and engineering.

3. What is a test function in the context of Fourier transformation?

In the context of Fourier transformation, a test function is a mathematical function that is used to test the properties and behaviors of the Fourier transformation. It is usually a well-behaved function that is infinitely differentiable and has compact support.

4. How is the Fourier transformation derived?

The Fourier transformation is derived from the Fourier series, which represents a periodic function as a sum of sine and cosine functions. The Fourier transformation extends this concept to non-periodic functions by allowing for an infinite range of frequencies instead of just a finite set.

5. What are some applications of Fourier transformation?

Fourier transformation has numerous applications in various fields, such as signal processing, image processing, data compression, and solving differential equations. It is also used in spectroscopy to analyze the frequencies present in a signal and in crystallography to determine the structure of crystals.

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