Solving 10-Point DFT of Shifted x[n] Sequence

In summary, to find the DFT of x[n] = x[n+5] with N = 10, we can use the relevant equation and the given six points of the DFT of the original sequence to calculate the remaining four points by taking the conjugate of the first six points. This is due to the symmetry property of DFT for real-valued inputs.
  • #1
elyons
10
1
Problem:

The first six values of the 10-point DFT of a real-valued sequence x(n) are given by

{10, −2 + j3, 3 + j4, 2 − j3, 4 + j5, 12}

Determine the DFT of x[n] = x[n+5] (10 point sequence)

Relevant Equations:

DFT(x[n-m]) = exp(-j*(2pi/N)*k*m) * X(k)
where N = 10 ; m = -5

Attempt:
Using the relevant equation calculating 6 points of the DFT from the shifted input is straight forward as X(k) is given 0<=k<=5 from the six point DFT series given.
I am failing to see how to calculate the 10 point series however. My intuition is that it has something to do with the periodicity of the DFT but I cannot see any patterns emerging from shifting the input. The magnitudes of the coefficients don't seem to change but their angles due, Still I can not spot any patterns...
 
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  • #2
I figured it out! In case anyone gets held up by something similar,

By paying attention to the symmetry property of DFT for a real valued input X(n) = X*(N-n) where X represents the DFT coefficients and N is the fundamental period, in this case 10, the remaining coefficients (n = 6:9) can be determined
 

What is a 10-Point DFT?

A 10-Point DFT (Discrete Fourier Transform) is a mathematical technique used in signal processing to convert a discrete sequence of time-domain samples into its equivalent representation in the frequency domain. It is commonly used in analyzing and manipulating digital signals in various applications such as audio and image processing.

What is a shifted x[n] sequence?

A shifted x[n] sequence refers to a discrete signal in the time domain that has been shifted or delayed by a certain number of samples. This can be represented mathematically as x[n-k], where k is the number of samples by which the signal is shifted.

Why is it important to solve the 10-Point DFT of a shifted x[n] sequence?

Solving the 10-Point DFT of a shifted x[n] sequence allows us to analyze the frequency components of a signal that has been shifted in the time domain. This can be useful in applications such as filtering, noise reduction, and signal reconstruction.

How is the 10-Point DFT of a shifted x[n] sequence calculated?

The 10-Point DFT of a shifted x[n] sequence can be calculated by multiplying the shifted signal with a complex exponential function at different frequencies and then summing the results. This process is repeated for each frequency component within the range of interest.

What are some common methods for solving the 10-Point DFT of a shifted x[n] sequence?

Some common methods for solving the 10-Point DFT of a shifted x[n] sequence include using the Fast Fourier Transform (FFT) algorithm, which is a more efficient way of calculating the DFT, and using various mathematical formulas and techniques such as the Discrete Fourier Series and the Discrete Fourier Transform definition.

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