Math Problem Statement
Compute the 8-point DFT of the sequence x[n] = 1 2 3 4 0 0 0 0 ↑
Using the radix-2 DIT algorithm. Follow exactly the corresponding signal flow graphs and keep track of all the intermediate quantities by putting them on the diagram.
Solution
To compute the 8-point Discrete Fourier Transform (DFT) of the sequence using the radix-2 Decimation-In-Time (DIT) algorithm, we need to follow the steps of the Fast Fourier Transform (FFT) algorithm carefully, which breaks the problem into smaller parts through butterfly computations.
Step-by-Step Procedure for Radix-2 DIT FFT
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Input sequence:
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Rearrange input sequence in bit-reversed order: For an 8-point sequence, the bit-reversed indices for the original indices are:
Rearranging the input sequence according to these bit-reversed indices:
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First stage of the butterfly computations: This stage involves 4 butterfly computations, where we combine pairs of values.
[ \text{Butterfly computation: } X[k] = x[n] + W_N^k \cdot x[n+N/2] ]
For this stage, and are the twiddle factors. However, for the first stage, we only need to add/subtract the values as the twiddle factors for the first stage are all 1.
\text{Butterfly 1: } & (1, 0) \Rightarrow 1+0 = 1 \text{ and } 1-0 = 1 \\ \text{Butterfly 2: } & (3, 0) \Rightarrow 3+0 = 3 \text{ and } 3-0 = 3 \\ \text{Butterfly 3: } & (2, 0) \Rightarrow 2+0 = 2 \text{ and } 2-0 = 2 \\ \text{Butterfly 4: } & (4, 0) \Rightarrow 4+0 = 4 \text{ and } 4-0 = 4 \\ \end{aligned}$$ After this stage, the intermediate output is: $$\{1, 1, 3, 3, 2, 2, 4, 4\}$$ -
Second stage of the butterfly computations: Now, in this stage, we use the twiddle factors for the 8-point FFT. The twiddle factors for are:
Perform the butterfly computations using these twiddle factors:
[ \begin{aligned} \text{Butterfly 1: } & (1, 3) \Rightarrow 1 + 3 = 4 \text{ and } 1 - 3 = -2 \ \text{Butterfly 2: } & (2, 4) \Rightarrow 2 + 4 = 6 \text{ and } 2 - 4 = -2 \ \text{Butterfly 3: } & \text{Apply } W_8^1 \text{ to the second half of each pair} \ & (1 + j3) \text{ and } (2 + j4) \end{aligned} }
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Math Problem Analysis
Mathematical Concepts
Discrete Fourier Transform
Radix-2 Decimation-In-Time Algorithm
Fast Fourier Transform
Complex Numbers
Formulas
X[k] = x[n] + W_N^k * x[n + N/2]
W_N^k = e^(-j 2πk/N)
Theorems
Discrete Fourier Transform
Radix-2 FFT Algorithm
Suitable Grade Level
University Level (Undergraduate)