DFT of a finite lengt sequence

In summary, the conversation discusses the computation of the 5-point DFT and inverse DFT of a given sequence x[n]. It also asks for the determination of the sequence y[n] and how to choose N-point DFTs for the two-step procedure in order to obtain y[n] as the product of x[n] and itself. The attempted solution involves substituting values and using the DFT transform pair, but results in a complicated expression containing sums of complex exponentials that may be difficult to simplify.
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Homework Statement



Consider the finite length x[n]= 2δ[n]+δ[n-1]+δ[n-3]

We perform the following operation on this sequence:

(i) We compute the 5-point DFT X[k]
(ii) We compute a 5-point inverse DFT of Y[k]=X[k]2

a) Determine the sequence y[n] for n= 0, 1, 2, 3, 4
b) If N-point DFTs are used in the two step pocedure, how should we choose N so that y[n]=x[n]*x[n] for 0 ≤ n ≤ N-1?

Homework Equations



DFT transform pair:

[tex]X[k]=\sum_{n=0}^{N-1}x[n]e^{(-j\frac{2π}{N}kn)}[/tex]

[tex]x[n]=\frac{1}{N}\sum_{k=0}^{N-1}X[k]e^{(j\frac{2π}{N}kn)}[/tex]

The Attempt at a Solution



a)

[tex]X[k]=\sum_{n=0}^{4}x[n]e^{(-j\frac{2π}{5}kn)}=2 + e^{-j\frac{2π}{5}k} + e^{-j\frac{2π}{5}3k}[/tex]

Then for calculation for Y[k] we substitute (2*pi/5)=a

[tex]Y[k]= X[k]^{2} = 4 + 4e^{-jak}+2e^{-j4ak}+4e^{-j3ak}+e^{-j2ak}+e^{-j6ak}[/tex]

Now to get y[n] through:

[tex]y[n]=\frac{1}{N}\sum_{k=0}^{4}X[k]^{2}e^{(j\frac{2π}{5}kn)}[/tex]

gives us a very complicated expression contained with sums of complex exponentials. It seems extremely difficult from here to simplify it so i can calculate y[n] for n=0,1,2,3,4
 
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  • #2
gives us a very complicated expression contained with sums of complex exponentials. It seems extremely difficult from here to simplify it so i can calculate y[n] for n=0,1,2,3,4P

Please post the expression that you obtained but found difficult to simplify. From what I remember in early college, these problems are usually a ton of tedious algebra, so you may not be far off.
 

1. What is DFT of a finite length sequence?

The Discrete Fourier Transform (DFT) of a finite length sequence is a mathematical algorithm used to convert a discrete signal in the time domain into a discrete signal in the frequency domain.

2. How is DFT different from Fourier Transform?

DFT is used to analyze discrete signals, while Fourier Transform is used to analyze continuous signals. DFT also has a finite number of samples, while Fourier Transform has an infinite number of samples.

3. What is the purpose of using DFT on a finite length sequence?

The purpose of using DFT on a finite length sequence is to analyze the frequency components present in the signal and identify any periodic patterns or frequencies.

4. What is the mathematical formula for DFT of a finite length sequence?

The mathematical formula for DFT of a finite length sequence is: X(k) = Σ x(n)e^(-i2πnk/N), where x(n) is the input sequence, N is the length of the sequence, and k is the frequency index.

5. What are some applications of DFT of a finite length sequence?

DFT of a finite length sequence is commonly used in applications such as signal processing, image processing, audio analysis, and data compression. It is also used in various fields of science and engineering for data analysis and pattern recognition.

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