Can an IIR filter be applied by convoluting a signal with its impulse response?

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In summary, FIR filters use convolution and have a finite impulse response, while IIR filters are recursive and have an infinite impulse response. However, if you convolute the response of an IIR filter with a signal, you still get a linear phase.
  • #1
sdfzz
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Hi all..

I'm a new to filters and I need some help understanding filters (I'm in mechanical engineering)

So far, I've found out that FIR filters use convolution and has a finite impulse response.

On the other hand, IIR filters are recursive and have an infinite impulse response.

But, what if I get the impulse response of an IIR filter (Butterworth, for example) and convolute the response with a signal? (given that I use only a part of the infinite signal).

Does this still count as an IIR filtering? Can I apply an IIR filter this way?

Any help would be appreciated.

Thank you
 
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  • #2
Well - taking the convolution sum and truncating it to some finite range is effectively taking an FIR approximation of a given IIR filter, which is actually one of the techniques to design FIR filters.
As a practical way to model a system, it's ok, it can even be pretty accurate - eventually any IIR impulse response decreases to a certain level bellow which the quantization makes it effectively zero, but theoretically it is wrong, and off course using the recursive way to calculate the response is always more accurate than approximating with FIR.
 
  • #3
Thank you for your reply :)
 
  • #4
Can I ask one more question?

If I have a low pass filter, whose transfer function is

H(s) = a/(a+s),

It it an IIR filter or FIR filter?
 
  • #5
It is neither.

The discrete-time versions are an approximation to the continuous transfer function.

The FIR approximation will come as close as you want to analog. The IIR version is very good but not exactly the same.

The IIR version of that filter includes a zero in the numerator at the nyquist frequency.

It's roughly y(n+1) = b*y(n) + c*(x(n)-x(n-1)).
 
  • #6
Thank you for your reply and sorry for keep asking...

The equation I'm dealing with contains a convolution, like A = f*B, where B is the input signal and f is the impulse response of a filter.

Does this mean that I am forced to use FIR filtering and no Butterworth or Chebyshev for me? (man... they look so attractive)

Also, Butterworth has a nonlinear phase, but FIR filters have a linear phase. However, if I use the impulse response of the Butterworth to do convolution (which is FIR filtering), do I still get a linear phase?

Thank you
 
  • #7
If you must convolve then yes FIR is required. Are you sure you must convolve?

You cannot get linear phase from an IIR.
 
  • #8
Sadly, yes. I must convolve...

Will there be any advantages of taking FIR approximation of IIR filters?
 
  • #9
Antiphon said:
The IIR version of that filter includes a zero in the numerator at the nyquist frequency.

not necessarily. if the analog filter was digitized using the bilinear transform, then it's true. but not necessarily if it was converted from analog to digital by other means (like Impulse Invariant).
 
  • #10
Thank you all for your help :)
 

Related to Can an IIR filter be applied by convoluting a signal with its impulse response?

What is an IIR filter?

An IIR (Infinite Impulse Response) filter is a type of digital filter that uses previous outputs to calculate current outputs. This creates a feedback loop, allowing the filter to have an infinite impulse response.

What is an FIR filter?

An FIR (Finite Impulse Response) filter is a type of digital filter that only uses previous inputs to calculate current outputs. This means that the filter has a finite impulse response and does not create a feedback loop.

What is the main difference between IIR and FIR filters?

The main difference between IIR and FIR filters is that IIR filters use a feedback loop to calculate outputs, while FIR filters only use previous inputs. This can result in different frequency responses and phase shifts.

Which type of filter is better for removing noise from a signal?

It depends on the specific application, but in general, FIR filters are better at removing noise from a signal because they do not create a feedback loop that can amplify the noise.

How do I choose between an IIR and FIR filter for my application?

The choice between an IIR and FIR filter depends on the specific requirements of your application, such as the desired frequency response, phase shift, and computational resources available. It is important to carefully consider these factors and consult with a digital signal processing expert if needed.

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