Hilbert Transform Homework: Show Envelope is |m(t)|

In summary: This means that the imaginary part of the analytic signal is the Hilbert transform of ##h(t)##, which is ##\hat{h}(t) = m(t)\sin(2\pi\nu_c t)##. The envelope of ##h(t)## is then given by ##|m(t)|##. In summary, for a real, band-limited function ##m(t)## and ##\nu_v > \nu_m,## the Hilbert transform of ##h(t) = m(t)\cos(2\pi\nu_c t)## is ##\hat{h}(t) = m(t)\sin(2\pi\nu_c t)##, and the envelope of ##h(t
  • #1
roam
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Homework Statement



For a real, band-limited function ##m(t)## and ##\nu_v > \nu_m,## show that the Hilbert transform of

$$h(t) = m(t) cos(2\pi \nu_c t)$$

is

$$\hat{h}(t) = m(t) sin(2 \pi \nu_c t),$$

and therefore the envelope of ##h(t)## is ##|m(t)|.##

Homework Equations



Analytic signal for a a real function ##f(t)## with Fourier transform ##F(\nu)## is given by

##f_a (t) = 2 \int^\infty_0 F(\nu) \exp(j 2 \pi \nu t).##

Modulation property of the Fourier transform

##f(t) \cos(2\pi \nu_0 t) \iff \frac{1}{2} \left( F(\nu + \nu_0) + F(\nu - \nu_0) \right)##

The Attempt at a Solution



The problem asks to compute the analytic signal from the Fourier transform of ##h(t)##, so I think I need to use the equation above for finding the analytic signal:

$$h_a (t) = 2 \int^\infty_0 \Big[ H(\nu) \Big] e^{-j 2 \pi \nu t} \ d\nu = 2 \int^\infty_0 \Big[ \int^\infty_{-\infty} m(t) \cos(2 \pi \nu_c t) e^{-j2 \pi \nu t} dt \Big] e^{-j 2 \pi \nu t} \ d\nu \ (i)$$

Furthermore, we are told that ##m(t)## is band-limited, which means ##M(\nu) = 0## for ##|\nu| > \nu_m.## So perhaps we can use the above property to write (i) as

$$h_a (t) = 2 \int^\infty_0 \Big[\frac{1}{2} \left( M(\nu + \nu_c) + M(\nu - \nu_c) \right) \Big] e^{-j 2 \pi \nu t} \ d\nu$$

Is this correct so far?

If this is correct, how do I simplify this further to find the imaginary part \hat{h}(t) (Hilbert transform)? Do I simply need to write the exponential as sine and cosine? :confused:

Any help would be greatly appreciated.
 
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  • #2
Thank you!Yes, you are on the right track. To simplify further, you can use the fact that the Fourier transform is symmetric, i.e. ##M(-\nu) = M(\nu)##. This means that the second term in the brackets will cancel out with the first term, leaving you with just ##M(\nu + \nu_c)## in the integral. Then, you can use the modulation property of the Fourier transform to write this as ##\frac{1}{2}M(\nu)##, giving you the final result of ##h_a(t) = m(t)\sin(2\pi\nu_c t)##.
 

Related to Hilbert Transform Homework: Show Envelope is |m(t)|

1. What is the Hilbert Transform?

The Hilbert Transform is a mathematical operation that takes a complex-valued function as input and produces another complex-valued function as output. It is used to analyze the frequency content of a signal and is commonly used in signal processing and communication systems.

2. What is the purpose of the Hilbert Transform?

The purpose of the Hilbert Transform is to provide a representation of a signal that separates its amplitude and phase components. This can be useful in analyzing the frequency content of a signal and in applications such as signal filtering and demodulation.

3. What is the envelope of a signal?

The envelope of a signal is a curve that represents the upper or lower bounds of the amplitude variations of the signal. It is often used to visualize the slowly varying amplitude of a high-frequency signal.

4. How is the envelope calculated using the Hilbert Transform?

The envelope of a signal can be calculated from its Hilbert Transform by taking the absolute value of the transformed signal. This results in a real-valued signal that represents the envelope of the original signal.

5. Can you show an example of using the Hilbert Transform to calculate the envelope of a signal?

Yes, for example, if we have a signal m(t) = cos(2πft), we can calculate its Hilbert Transform as H(m(t)) = sin(2πft). Taking the absolute value of this transformed signal, we get the envelope of m(t) as |m(t)| = |cos(2πft)| = 1. This means that the envelope of m(t) remains constant at 1, while the amplitude of the original signal varies sinusoidally with frequency f.

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