Compute Discrete Time Fourier Transform

In summary, the conversation discusses finding the DTFT of a signal using properties and the property of modulation. The conversation includes computations and substitution, but the correct solution has not been found yet.
  • #1
nacho-man
171
0
Hi bros,

so I feel like I am very close, but cannot find out how to go further.

Q.1 Compute the DTFT of the following signals, either directly or using its properties (below a is a fixed constant |a| < 1):

for $x_n = a^n \cos(\lambda_0 n)u_n$ where $\lambda_0 \in (0, \pi)$ and
$u_n$ is the step function, i.e $u_n = 1 $ for $n\ge 0 $ and $0$ otherwise.
so,

$X(e^{i \lambda}) = \sum_{n=0}^{+\infty} x_n e^{-i\lambda n}$$X(e^{i \lambda}) = \sum_{n=0}^{+\infty} a^n \cos(\lambda_0 n) e^{-i\lambda n}$

using euler's formula: $\cos(\lambda_0 n)$ = $\frac{e^{i\lambda_0 n}+ e^{-i\lambda_0 n}}{2} $

so $X(e^{i \lambda}) = \frac{1}{2} \sum_{n=0}^{+\infty} (a e^{-i \lambda}( e^{i\lambda_0}+ e^{-i\lambda_0}))^n $

which gives

$\frac{1}{2} \sum_{n=0}^{+\infty} a^n(e^{i \lambda_0 - i\lambda} + e^{-i \lambda_0 - i\lambda})^n)$

and now i am stuck
.
i think i have it right upto this point, but i do not know how to proceed.

also in our notes, he has said to use the property called modulation, which meanswhere we have $x^n e^{i \lambda_0 n}$ the DTFT will be of the form $X(e^{i(\lambda-\lambda_0)})$ANY HELP IS APPRECIATED! thank you!
 
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  • #2
Hi nacho! :)

nacho said:
$X(e^{i \lambda}) = \sum_{n=0}^{+\infty} a^n \cos(\lambda_0 n) e^{-i\lambda n}$

using euler's formula: $\cos(\lambda_0 n)$ = $\frac{e^{i\lambda_0 n}+ e^{-i\lambda_0 n}}{2} $

so $X(e^{i \lambda}) = \frac{1}{2} \sum_{n=0}^{+\infty} (a e^{-i \lambda}( e^{i\lambda_0}+ e^{-i\lambda_0}))^n $

Not so fast.
Let's first do only the substitution.

$$X(e^{i \lambda}) = \sum_{n=0}^{+\infty} a^n \cdot \frac{1}{2} (e^{i\lambda_0 n}+ e^{-i\lambda_0 n}) \cdot e^{-i \lambda n} $$

This is different from what you have. :eek:
which gives

$\frac{1}{2} \sum_{n=0}^{+\infty} a^n(e^{i \lambda_0 - i\lambda} + e^{-i \lambda_0 - i\lambda})^n)$

and now i am stuck
.
i think i have it right upto this point, but i do not know how to proceed.

Let's redo that and simplify to:
$$X(e^{i \lambda})
= \frac{1}{2} \sum_{n=0}^{+\infty} a^n (e^{-i(\lambda - \lambda_0) n}+ e^{-i(\lambda + \lambda_0) n})
= \frac{1}{2} \sum_{n=0}^{+\infty} a^n e^{-i(\lambda - \lambda_0) n} + \frac{1}{2} \sum_{n=0}^{+\infty} a^n e^{-i(\lambda + \lambda_0) n}
$$
also in our notes, he has said to use the property called modulation, which meanswhere we have $x^n e^{i \lambda_0 n}$ the DTFT will be of the form $X(e^{i(\lambda-\lambda_0)})$

Can you apply this now? (Wondering)
 

FAQ: Compute Discrete Time Fourier Transform

What is a discrete time Fourier transform (DTFT)?

The discrete time Fourier transform is a mathematical tool used to analyze the frequency components of a discrete-time signal. It converts a signal from its original time domain into the frequency domain, allowing us to better understand the frequency content of the signal.

How is a discrete time Fourier transform different from a continuous time Fourier transform?

A discrete time Fourier transform operates on discrete-time signals, which are signals that are only defined at certain points in time. In contrast, a continuous time Fourier transform operates on continuous-time signals, which are signals that are defined at every point in time.

What is the mathematical formula for computing a discrete time Fourier transform?

The mathematical formula for computing a discrete time Fourier transform is given by the sum of the signal multiplied by a complex exponential function. This formula is known as the Discrete Fourier Transform (DFT) and is commonly denoted as X(k) = Σx(n)e-j2πkn/N, where N is the length of the signal and k is the frequency index.

What are the applications of a discrete time Fourier transform?

The discrete time Fourier transform has many practical applications in signal processing, including spectral analysis, filtering, and signal reconstruction. It is also used in various fields such as telecommunications, audio and image processing, and control systems.

What are some limitations of the discrete time Fourier transform?

One limitation of the discrete time Fourier transform is that it assumes the signal is periodic, which may not always be the case in real-world applications. It also has a finite frequency resolution, meaning it cannot accurately capture frequency components that are close together. Additionally, the computation of the discrete time Fourier transform can be time-consuming for larger signals.

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