LTI systems- frequency response

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Discussion Overview

The discussion revolves around the frequency response of a "brick-wall" band pass filter, with participants exploring its mathematical representation, impulse response, and implications of causality. The conversation includes attempts to derive expressions and clarify concepts related to linear time-invariant (LTI) systems.

Discussion Character

  • Technical explanation
  • Homework-related
  • Debate/contested

Main Points Raised

  • One participant requests assistance in finding the expression for the frequency response of a band pass filter.
  • Another participant provides a piecewise definition of the frequency response H(f) and notes the non-causality of the ideal filter.
  • Several participants discuss the inverse Fourier transform to find the impulse response, with differing opinions on the correct form of H(f) to use.
  • There are claims that the impulse response of an ideal bandpass filter is the sum of two sinc functions, while others argue it is a single sinc function.
  • Participants debate the relationship between frequency response and impulse response, with some confusion about the limits of integration and the nature of the functions involved.
  • One participant suggests using Euler's formula to simplify the exponential terms in the context of the impulse response.
  • Another participant questions whether two different integrals are needed for the two sinc functions associated with the bandpass filter.
  • There is a discussion about the relationship between low-pass and high-pass filters, and how they can be expressed in terms of each other.

Areas of Agreement / Disagreement

Participants express differing views on the form of the impulse response for the bandpass filter, with no consensus reached on whether it consists of one or two sinc functions. The discussion remains unresolved regarding the correct approach to deriving the impulse response and the implications of causality.

Contextual Notes

Some participants highlight the limitations of ideal filters, noting that they cannot be physically realized. There are also mentions of the need for careful evaluation of integrals and the importance of understanding the relationship between frequency and impulse responses.

Who May Find This Useful

This discussion may be useful for students and practitioners interested in signal processing, particularly those studying linear time-invariant systems and filter design.

Davidlong
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I have attached an image of a ''brick-wall'' band pass filter. Can someone please help me find the expression of frequency response for it?


Homework Statement


Homework Equations


The Attempt at a Solution

 

Attachments

  • Brick-wall bpf filter.jpg
    Brick-wall bpf filter.jpg
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Well, acctually, you're looking at it:

H(f) = 0, f < f1
H(f) = 1, f1 < f < f2
H(f) = 0, f > f1
where f2 - f1 = BW.
This filter BTW is unrealizable since its input-output relationship is not causal ...

From a web page:

<< Impulse Response and Causality
• All the impulse responses of ideal filters are
sinc functions, or related functions, which
are infinite in extent
• Therefore all ideal filter impulse responses
begin before time, t = 0
• This makes ideal filters non-causal
• Ideal filters cannot be physically realized,
but they can be closely approximated >>
 
Davidlong, in the future please fill out the question form completely. It is a rule of the Forum that you must show your attempt at a solution before receiving assistance.
 
rude man said:
Well, acctually, you're looking at it:

H(f) = 0, f < f1
H(f) = 1, f1 < f < f2
H(f) = 0, f > f1
where f2 - f1 = BW.
This filter BTW is unrealizable since its input-output relationship is not causal ...

From a web page:

<< Impulse Response and Causality
• All the impulse responses of ideal filters are
sinc functions, or related functions, which
are infinite in extent
• Therefore all ideal filter impulse responses
begin before time, t = 0
• This makes ideal filters non-causal
• Ideal filters cannot be physically realized,
but they can be closely approximated >>

I have the following equation for finding the impulse response function. The equation is the inverse Fourier transform of the H(f) equation.(infinity and -infinity are the limits) h(τ)=∫e(2∏jfτ)H(f)df.

I replaced the limits with f2 and f1 which represent F+BW/2 and F-BW/2 respectively.

For the integral i get [H(f)/2∏jf]*[e(2∏jfF2)-e(2∏jfF1)].

I don't understand what value i should use for H(f), should it just be 1? And would that be the full expression for the impulse response or can it be simplified further?


Thanks
 
Yes, H(f) is 1 in that interval. You can factor the exponentials and then simplify (think about trig functions).
 
This is the code I've written in Matlab;

Fc=500; %filter frequency
BW=80; %bandwidth frequency
F2=Fc+BW/2; %upper limit
F1=Fc-BW/2; %lower limit
Fs=11025; %sampling frequency
Ts=1/Fs; %sampling time

IRF=(1/(2*pi*1j*Ts))*(exp(2*pi*1j*F2*Ts)-exp(2*pi*1j*F1*Ts)); %impulse response
FRF=(1/(-2*pi*1j*Ts))*(exp(-2*pi*1j*F2*Ts)-exp(-2*pi*1j*F1*Ts)); %frequency response

A1=abs(FRF);
theta1=-angle(FRF);

figure(1)
plot(Fc,A1)
title('System A')
xlabel('frequency')
ylabel('amplitude response')

figure(2)
plot(Fc,theta1)
title('System A')
xlabel('frequency in Hz')
ylabel('phase response')I'm meant to shift the curve to t>0, truncate h(t) to some reasonable finite times and sample h(t) at a sampling time of Ts=1/Fs which is supposed to give a set of {h(n)} coefficients for the filter. I think I've done the sampling but I'm not sure on which variables to adjust to achieve the shift and truncating.
 
You have made some errors:

1) Your code for FRF is incorrect. The FRF is H(f), which you were given at the start. (See rude man's post).
2) You did not properly evaluate the integral that gives h(t). You can't put the limits in before you evaluate the integral, and, BTW, the answer should be a function of t, not f.

Perhaps it would be helpful to reread the parts of your text that describe what frequency and impulse response functions are, and how they are related. Then look at rud man's post and mine, and try to work the problem again.
 
Davidlong said:
I have the following equation for finding the impulse response function. The equation is the inverse Fourier transform of the H(f) equation.(infinity and -infinity are the limits) h(τ)=∫e(2∏jfτ)H(f)df.

I replaced the limits with f2 and f1 which represent F+BW/2 and F-BW/2 respectively.

For the integral i get [H(f)/2∏jf]*[e(2∏jfF2)-e(2∏jfF1)].

I don't understand what value i should use for H(f), should it just be 1? And would that be the full expression for the impulse response or can it be simplified further?


Thanks

The impulse reponse to an ideal bandpass filter is the sum of two sinc functions, one for each corner frequency, as you may be able to determine by taking the inverse Fourier of H(f). The impulse response has infinite delay and the output can build up to infinity, so it's not of much use except for theoretical work.

Of course there are many realizable filter types that can approximate the ideal bandpass filter.
 
rude man said:
The impulse reponse to an ideal bandpass filter is the sum of two sinc functions, one for each corner frequency, as you may be able to determine by taking the inverse Fourier of H(f).
This is incorrect. It is a single sinc function, which the OP can determine by factoring the exponential terms and applying a trig identity as I suggested.

rude man said:
The impulse response has infinite delay and the output can build up to infinity, so it's not of much use except for theoretical work.
To be precise, the theoretical impulse response has finite amplitude, but extends in time from -∞ to ∞.
 
  • #10
marcusl said:
This is incorrect. It is a single sinc function, which the OP can determine by factoring the exponential terms and applying a trig identity as I suggested.

To be precise, the theoretical impulse response has finite amplitude, but extends in time from -∞ to ∞.

It is two sinc functions. You may be thinking of a low-pass.
 
  • #11
Yes it's a low pass filter. Do I use eulers formula to factor the exponentials and then apply the trig function?

For the frequency response the equation ends in dt, so its a function of t. For impulse response it ends in df so the impulse response is a function of f. Am i correct on this?
 
  • #12
Davidlong said:
Yes it's a low pass filter. Do I use eulers formula to factor the exponentials and then apply the trig function?

For the frequency response the equation ends in dt, so its a function of t. For impulse response it ends in df so the impulse response is a function of f. Am i correct on this?

It's a bandpass, not a lowpass. Look at your figure more carefully.

You have it backwards. ∫f(t)exp(-jwt)dt = F(f) and ∫F(f)exp(jwt)df = f(t).
 
  • #13
So if there's 2 sinc functions do i have 2 different integrals? So for example with limits Fc to fc-BW/2 and fc+BW/2 to Fc?

For a low pass filter the sinc function is 2.Fc.sinc(2.Fc.t) when the limits are Fc and -Fc. But I'm not sure how to achieve this if it's a band-pass filter.
 
  • #14
Davidlong said:
So if there's 2 sinc functions do i have 2 different integrals? So for example with limits Fc to fc-BW/2 and fc+BW/2 to Fc?

For a low pass filter the sinc function is 2.Fc.sinc(2.Fc.t) when the limits are Fc and -Fc. But I'm not sure how to achieve this if it's a band-pass filter.

EDIT:
Can you express an ideal high-pass filter Hh(f) in terms of an ideal low-pass filter Hl(f) plus a constant, the cutoff frequency being the same in both cases? Then draw a picture of Hl and another of Hf where the low-pass cutoff frequency is f1 and the high-pass cutoff frequency is f2, f2 > f1.
 
Last edited:
  • #15
The H(f) you are given is a (frequency)-shifted version of a low-pass filter. Now, you already know the frequency response for a low-pass filter, and I bet your teacher covered a rule that relates shifting in the frequency domain to a simple operation in the time domain. (If not, look at the table in your textbook and I am sure you will find that property of the Fourier transform.)
 

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