Reward, test everyone Fourier transform question 100

To realize the Fourier transform of the discrete impulse signal with period n, it is necessary to discretize the time domain and frequency domain step by step. In the first step, the time domain is discretized, we get the discrete-time Fourier transform (DTFT), and the spectrum is periodized; In the second step, the frequency domain is discretized, and we obtain the discrete periodic Fourier series (DFS), and the time domain is further periodized. In the third step, considering the time and frequency domains of periodic discretization, we will take only one periodic study, which is known as the discrete Fourier transform (DFT).

Aren't you the specific topic of the fourier transformation?

LS are all masters, and I don't understand it very well.

Discrete function f(x)=c, apply the formula f(f)(s)=1 root number 2 faction * integral c*exp(-sx)dx=1 s*1 root2pi*(exp(ns)-exp(-ns))).

Looks like a sine wave.

Khan, DTFT appears to be a discrete-time Fourier series, and the Fourier transform is used to find partial differential equations and green-f. However, it is possible that the fields are different, and the statements are different.

I don't know if the period n you said is defined as follows:

t=1;x(n)=1,n=0;=0,n=1;..=1,n=nx(w)=sigma[x(n)exp(-jnw)]=1+sigma(exp(-jknw)

I'm a physics student and don't know much about your subject...

Known: x[n]=

Find: x[n]=dft(x[n]).

Let the complex number w=e (-2 j n).

x[k]=∑x[i]*w^(k*i) (i=0 to n-1)k=0,1,2,..n-1)

Because only x[0]=1

So x[n]=

There are some of them. Although I don't understand. But it should be. My brother told me.

You can't map the formula here, you look for it in very detailed.

The answer is as follows:

Symbolic functions are not absolutely integrable, and there is no Fourier transform in the usual sense. It is possible to find it under the condition that the generalized function is considered, but it cannot be found with the defining formula f(jw) = f(t)e dt. It can be obtained by conjugate symmetry when u(t) is known.

In different fields of study, the Fourier transform has many different variant forms, such as continuous Fourier transform and discrete Fourier transform. Originally, Fourier analysis was proposed as a tool for analytical analysis of thermal processes.

1. The convolution of the knot silver contains the law. [ f1(t)*f2(t) ]f3(t) = according to the convolution equation. 2 Because f[f (t)]=2 j, using symmetry, there is a fight to know:

f[2 /jω]=2*π*f（-w)and for the symetrial property of f(t).f[2 /jω]=2*π*f（w)end

A Fourier transform is a linear combination of trigonometric functions (sine sum or cosine functions) or their integrals that satisfy certain conditions.

The Fourier transform can convert the originally difficult time-domain signals into easy-to-analyze frequency-domain signals (the spectrum of the signal), and some tools can be used to process and process these frequency-domain signals. Finally, the inverse Fourier transform can be used to convert these frequency-domain signals into time-domain signals.

Because of its good properties, the Fourier transform has a wide range of applications in physics, number theory, combinatorics, signal processing, probability, statistics, cryptography, acoustics, optics and other fields.