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Marcus Müller
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IveI've been working with Allan variance for a while and ImI'm not really super excited about is purpose.

I understand that noise time recordings, if they include flicker noise, diverge in time. In other words the standard deviation increases logarithmically, but why is this a problem? Modern computers can calculate the st dev as a function of window size without any problems for millions of data points.

The plot of Allan dev against observation time multiples is nice, but your data has to be very clean of deterministic signals otherwise very ugly things appear. Also you can see different noise process in the std dev vs window size also or PSD.

It seems to me that this tool was mainly useful decades ago when computer were much more limited and other problems like dead time in measurements existed.

Am I missing something?

Ive been working with Allan variance for a while and Im not really super excited about is purpose.

I understand that noise time recordings, if they include flicker noise, diverge in time. In other words the standard deviation increases logarithmically, but why is this a problem? Modern computers can calculate the st dev as a function of window size without any problems for millions of data points.

The plot of Allan dev against observation time multiples is nice, but your data has to be very clean of deterministic signals otherwise very ugly things appear. Also you can see different noise process in the std dev vs window size also or PSD.

It seems to me that this tool was mainly useful decades ago when computer were much more limited and other problems like dead time in measurements existed.

Am I missing something?

I've been working with Allan variance for a while and I'm not really super excited about is purpose.

I understand that noise time recordings, if they include flicker noise, diverge in time. In other words the standard deviation increases logarithmically, but why is this a problem? Modern computers can calculate the st dev as a function of window size without any problems for millions of data points.

The plot of Allan dev against observation time multiples is nice, but your data has to be very clean of deterministic signals otherwise very ugly things appear. Also you can see different noise process in the std dev vs window size also or PSD.

It seems to me that this tool was mainly useful decades ago when computer were much more limited and other problems like dead time in measurements existed.

Am I missing something?

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Ralph
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Is Allan variance still relevant?

Ive been working with Allan variance for a while and Im not really super excited about is purpose.

I understand that noise time recordings, if they include flicker noise, diverge in time. In other words the standard deviation increases logarithmically, but why is this a problem? Modern computers can calculate the st dev as a function of window size without any problems for millions of data points.

The plot of Allan dev against observation time multiples is nice, but your data has to be very clean of deterministic signals otherwise very ugly things appear. Also you can see different noise process in the std dev vs window size also or PSD.

It seems to me that this tool was mainly useful decades ago when computer were much more limited and other problems like dead time in measurements existed.

Am I missing something?