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Léo Léopold Hertz 준영
Léo Léopold Hertz 준영
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Which antialiasing filter before equalspacedequispaced sampling

I am using MIT-BIH arrhythmical database where I have a digital signal of 1200 Hz so 1200 samples per second. This means that analog filters have already applied to remove the frequencies over Nyquist frequency, so no aliasing.

However, I want to take equalspacedequispaced sampling, every two sample, simply by the following in Matlab

data([0:2:1200]);

I am reading Andre Quinquils' book Digital Signal Processing Using Matlab 2008:

It is always necessary to use an anti-aliasing filter before the sampling stage in order to avoid any spectral aliasing risk and to set an appropriate sampling frequency. In practice, a causal approximation of this ideal filter is used. Thus, depending on the chosen filter synthesis method, some imperfections are introduced, such as a passband amplitude ripple, a transition band and a stopband finite attenuation.

Does this mean that I need to apply a new anti-aliasing filter before the sampling stage in oder to avoid aliasing? I think the sampling stage here is the equalspaced sampling. I have not applied any new special anti-aliasing filter.

Which antialiasing filter can you use before equalspaced sampling stage?

Which antialiasing filter before equalspaced sampling

I am using MIT-BIH arrhythmical database where I have a digital signal of 1200 Hz so 1200 samples per second. This means that analog filters have already applied to remove the frequencies over Nyquist frequency, so no aliasing.

However, I want to take equalspaced sampling, every two sample, simply by the following in Matlab

data([0:2:1200]);

I am reading Andre Quinquils' book Digital Signal Processing Using Matlab 2008:

It is always necessary to use an anti-aliasing filter before the sampling stage in order to avoid any spectral aliasing risk and to set an appropriate sampling frequency. In practice, a causal approximation of this ideal filter is used. Thus, depending on the chosen filter synthesis method, some imperfections are introduced, such as a passband amplitude ripple, a transition band and a stopband finite attenuation.

Does this mean that I need to apply a new anti-aliasing filter before the sampling stage in oder to avoid aliasing? I think the sampling stage here is the equalspaced sampling. I have not applied any new special anti-aliasing filter.

Which antialiasing filter can you use before equalspaced sampling stage?

Which antialiasing filter before equispaced sampling

I am using MIT-BIH arrhythmical database where I have a digital signal of 1200 Hz so 1200 samples per second. This means that analog filters have already applied to remove the frequencies over Nyquist frequency, so no aliasing.

However, I want to take equispaced sampling, every two sample, simply by the following in Matlab

data([0:2:1200]);

I am reading Andre Quinquils' book Digital Signal Processing Using Matlab 2008:

It is always necessary to use an anti-aliasing filter before the sampling stage in order to avoid any spectral aliasing risk and to set an appropriate sampling frequency. In practice, a causal approximation of this ideal filter is used. Thus, depending on the chosen filter synthesis method, some imperfections are introduced, such as a passband amplitude ripple, a transition band and a stopband finite attenuation.

Does this mean that I need to apply a new anti-aliasing filter before the sampling stage in oder to avoid aliasing? I think the sampling stage here is the equalspaced sampling. I have not applied any new special anti-aliasing filter.

Which antialiasing filter can you use before equalspaced sampling stage?

Source Link
Léo Léopold Hertz 준영
Léo Léopold Hertz 준영
  • 143
  • 7

Which antialiasing filter before equalspaced sampling

I am using MIT-BIH arrhythmical database where I have a digital signal of 1200 Hz so 1200 samples per second. This means that analog filters have already applied to remove the frequencies over Nyquist frequency, so no aliasing.

However, I want to take equalspaced sampling, every two sample, simply by the following in Matlab

data([0:2:1200]);

I am reading Andre Quinquils' book Digital Signal Processing Using Matlab 2008:

It is always necessary to use an anti-aliasing filter before the sampling stage in order to avoid any spectral aliasing risk and to set an appropriate sampling frequency. In practice, a causal approximation of this ideal filter is used. Thus, depending on the chosen filter synthesis method, some imperfections are introduced, such as a passband amplitude ripple, a transition band and a stopband finite attenuation.

Does this mean that I need to apply a new anti-aliasing filter before the sampling stage in oder to avoid aliasing? I think the sampling stage here is the equalspaced sampling. I have not applied any new special anti-aliasing filter.

Which antialiasing filter can you use before equalspaced sampling stage?