Ideal Filter - Windowed - DTFT/Highpass

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In summary, the goal of this problem was to prove that as N approaches infinity, the filter approaches the ideal high-pass differentiator. However, there was an error in the MATLAB code, causing the result to be a constant value instead of approaching the ideal filter. The correct result is H_3\left(e^{j\omega}\right) = -\sum_{n=-N/2}^{N/2} \frac{sin\left(\pi n - \frac{\pi}{2}\right)}{\pi \left(n-1/2\right)^2}e^{-j\omega n}.
  • #1
DSRadin
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Homework Statement


Given:
[itex]H_{dd}\left(e^{j\omega}\right)=j\omega e^{\frac{-j\omega}{2}}, \left|\omega\right|\le\pi[/itex]

Find: [itex]H_{3}\left(e^{j\omega}\right)[/itex] where
[itex]H_{3}\left(e^{j\omega}\right)[/itex] is the spectrum of [itex] h_{dd}\left(n\right)\left(W_N\left(n\right)\right) [/itex] and [itex] W_N\left(n\right)=1 for \frac{-N}{2}\le n \le \frac{N}{2} , [/itex] 0 else


Homework Equations


DTFT Synthesis: [itex] \frac{1}{2\pi}\int_{-\pi}^{\pi} H\left(e^{j\omega}\right)e^{j\omega n}d\omega [/itex]
[itex] DTFT Analysis: \sum_{n=\frac{-N}{2}}^{\frac{N}{2}} h(n)e^{-j\omega n} [/itex]

The Attempt at a Solution



Step 1: Synthesis [itex]h_{dd}\left(n\right)[/itex]. This is done through integration by parts and my result is:

[itex] h_{dd}(n)=-sin\left(\pi\left(n-\frac{1}{2}\right)\right) [/itex]

Step 2: Window - ok. [itex] -\frac{N}{2}\le n \le \frac{N}{2} [/itex] is the new range.

Step 3: DTFT windowed function result:
[itex] H_3\left(e^{j\omega}\right) = -\sum_{n=-N/2}^{N/2} \frac{sin\left(\pi n - \frac{\pi}{2}\right)}{\pi \left(n-1/2\right)^2}e^{-j\omega n} [/itex]

Really cool - but when plotted versus frequency, I get a constant, regardless of the size of N.
The goal of this problem was to prove that as N--> big that the filter approaches the ideal high-pass differentiator. I must have made a mistake somewhere but I'm not sure where, if anyone could see if they receive a different result I would be much obliged. Thanks!

-DR
 
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  • #2
Found my mistake - it turns out that the above is actually correct and corresponds to Sum( (-1)^(n-1/2)/(denom) * e^-jwn).

There was an error in my MATLAB code (ridiculous error) where my for loop looked like:

for i=length(n)

instead of

for i=1:length(n)

hence the reason I was only getting one constant value... You think it's some important mistake in your math and it turns out to be a typo.

Oh well, Go Bears.
 

FAQ: Ideal Filter - Windowed - DTFT/Highpass

1. What is an Ideal Filter?

An Ideal Filter is a theoretical filter that can completely remove unwanted frequencies from a signal without affecting the desired frequencies. It is characterized by a perfectly sharp transition between the passband and stopband, with no ripples or attenuation in the passband.

2. What is a Windowed Filter?

A Windowed Filter is a type of filter that uses a windowing function to smooth out the sharp edges of an Ideal Filter, resulting in a more practical and realizable filter. The windowing function is applied to the impulse response of the Ideal Filter, which helps to reduce the amplitude of the high frequency components.

3. What is the Discrete-Time Fourier Transform (DTFT)?

The Discrete-Time Fourier Transform (DTFT) is a mathematical tool used to analyze the frequency components of a discrete-time signal. It converts a discrete-time signal into a continuous frequency spectrum, allowing for analysis of the signal's frequency content.

4. How is a Highpass Filter different from a Lowpass Filter?

A Highpass Filter is a type of filter that allows high frequency components of a signal to pass through while attenuating or removing low frequency components. This is in contrast to a Lowpass Filter, which does the opposite by allowing low frequency components to pass through while attenuating high frequency components.

5. What are some applications of Ideal Filter - Windowed - DTFT/Highpass?

Ideal Filter - Windowed - DTFT/Highpass is commonly used in digital signal processing applications, such as audio and image processing, to remove unwanted noise or frequency components from a signal. It is also used in communications systems to filter out interference and improve signal quality.

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