Understanding Normalized Filters and Their Impact on Waveform Distortion

In summary, "normalized" means dividing by a base to allow for scaling, and understanding the process of calculating component values for filters is important in order to identify any errors in computer-generated values. Additionally, in order to preserve the wave shape, a filter with a phase shift that increases linearly with frequency is needed to provide equal time shift for all components. This ensures that the output waveform remains undistorted.
  • #1
jendrix
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Hello, I am learning about filters but I'm having trouble understanding what 'normalised' means and it's significance. I am using a LPF filter in a project and whilst there is software that will design it for you, I would also like to learn to calculate the values for myself and learn the significance of adjusting component values.

On a second note this got me wondering, if a filter incorporates a phase shift that changes as a function of frequency, wouldn't the input and output waveform change significantly?
 
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  • #2
jendrix said:
if a filter incorporates a phase shift that changes as a function of frequency, wouldn't the input and output waveform change significantly?
Yes, if you filter a waveform having components of different frequencies it can undergo distortion so the output wave shape may look very different from the input waveshape. To preserve the wave shape requires use of a filter where phase shift increases with frequency, and in a linear fashion across the passband, to give equal TIME SHIFT for the various components. Such a filter acts as a delay.
 
  • #3
jendrix said:
Hello, I am learning about filters but I'm having trouble understanding what 'normalised' means and it's significance. I am using a LPF filter in a project and whilst there is software that will design it for you, I would also like to learn to calculate the values for myself and learn the significance of adjusting component values.

On a second note this got me wondering, if a filter incorporates a phase shift that changes as a function of frequency, wouldn't the input and output waveform change significantly?

There are lowpass filter tables which give you "normalized" parts values, which means: The given values allow a corner frequency of 1 rad/sec.
Using a simple scaling process you can use these data for finding the parts values for any desired corner frequency (end of the pass band).

As to the second question: Of course, frequency-dependent amplitude changes are connected with a corresponding phase shift.
However, speaking of input and output waveforms, it is primarily the frequency-dependence of the various signal amplitudes within the spectrum of the applied wave which is responsible for the output waveform.
Example: A bandpass filtered square wave gives an output signal which looks - more or less - like a sinusoidal wave.
 
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  • #4
jendrix said:
I would also like to learn to calculate the values for myself and learn the significance of adjusting component values.
Bravo for you ! Learn to calculate them yourself so you know when a computer code is putting out gibberish.

"Normalize" usually means dividing by a base , perhaps center frequency for a bandpass, so that the example they're using to demonstrate works in % or multiples of base instead of the actual number.
Analogous to the "Per Unit" method used in power systems analysis.

As LvW said - it's just scaling .
 
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  • #5
LvW said:
There are lowpass filter tables which give you "normalized" parts values, which means: The given values allow a corner frequency of 1 rad/sec.
Using a simple scaling process you can use these data for finding the parts values for any desired corner frequency (end of the pass band).

As to the second question: Of course, frequency-dependent amplitude changes are connected with a corresponding phase shift.
However, speaking of input and output waveforms, it is primarily the frequency-dependence of the various signal amplitudes within the spectrum of the applied wave which is responsible for the output waveform.
Example: A bandpass filtered square wave gives an output signal which looks - more or less - like a sinusoidal wave.
Hello, I don't suppose you have any resources for this do you? It seems finding the component values yourself isn't typically done anymore but I would still like to understand the process.

Thanks
 
  • #6
jim hardy said:
Bravo for you ! Learn to calculate them yourself so you know when a computer code is putting out gibberish.

"Normalize" usually means dividing by a base , perhaps center frequency for a bandpass, so that the example they're using to demonstrate works in % or multiples of base instead of the actual number.
Analogous to the "Per Unit" method used in power systems analysis.

As LvW said - it's just scaling .

I'm starting to understand, I have been researching a Butterworth filters for a project. It will be a low pass with a corner frequency of 100 rad/sec. I assume scaling up isn't as simple as taking the normalised values and multiplying by 100?

Thanks
 
  • #7
You are close...

Consider a simple RC low pass filter. If you multiply the component values by 100 the corner frequency goes down not up.
 
  • #8
NascentOxygen said:
Yes, if you filter a waveform having components of different frequencies it can undergo distortion so the output wave shape may look very different from the input waveshape. To preserve the wave shape requires use of a filter where phase shift increases with frequency, and in a linear fashion across the passband, to give equal TIME SHIFT for the various components. Such a filter acts as a delay.
I am still trying to get my head around this. My immediate instinct was that if two waves of differing frequencies experienced a different phase shift then they would be out of phase with each other at the output?

Is it because the time period of for example a 10Hz waveform with a phase shift of 90o would give a time delay of 25ms therefore if you had a second waveform at 15Hz you would need a larger phase shift to account for a time delay of 25ms?

Thanks
 
  • #9
jendrix said:
Is it because the time period of for example a 10Hz waveform with a phase shift of 90o would give a time delay of 25ms therefore if you had a second waveform at 15Hz you would need a larger phase shift to account for a time delay of 25ms?
That's the idea. If everything experiences the exact same time delay, the filter acts like a delay line, and produces no wave-shape distortion. Of course, if you build a filter where all components in the input are passed across to the output with no alteration to their relative amplitudes and all experience a common time delay, it won't be doing much of what we commonly think of as "filtering".
 
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1. What are filters and how do they work?

Filters are tools used to selectively remove or enhance certain aspects of a signal or data set. They work by altering the frequency components of a signal, allowing certain frequencies to pass through while rejecting others. This can be done through mathematical operations or physical components such as capacitors and resistors.

2. What are the different types of filters?

There are various types of filters, including low-pass, high-pass, band-pass, and band-stop filters. Low-pass filters allow low frequencies to pass through while attenuating high frequencies, and vice versa for high-pass filters. Band-pass filters allow a certain range of frequencies to pass through, while band-stop (or notch) filters reject a specific range of frequencies.

3. What are some common applications of filters?

Filters are used in a wide range of applications, including audio and video processing, signal analysis, data compression, and noise reduction. They are also commonly used in electronic devices such as televisions, radios, and smartphones to improve the quality of signals and reduce interference.

4. How do I choose the right filter for my application?

The choice of filter depends on the specific requirements of your application. Factors to consider include the type of signal or data, the frequency range of interest, and the desired level of attenuation. It is important to carefully analyze these factors and consult with an expert to select the most suitable filter for your needs.

5. What are the limitations of filters?

Filters have certain limitations, such as signal distortion, phase shift, and noise added to the output signal. These limitations can affect the accuracy and quality of the filtered signal, and it is important to carefully consider them when designing a filter for a specific application. Additionally, filters have a limited frequency range in which they can effectively operate, so it is important to select a filter with an appropriate cutoff frequency for your signal.

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