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GlennA
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Gold
Part IV ?
GlennA   6/6/2012 2:26:24 PM
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Is there going to be a Part IV describing the 'anti-alias filter' ?

Jon Titus
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Blogger
Re: Part IV ?
Jon Titus   6/6/2012 3:08:06 PM
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Hi, Glenn.  Thanks for your question. I can cover anti-alias filters in another installment, but you'll find many good references and application notes.  Here's a link to one from Maxim: http://www.maxim-ic.com/app-notes/index.mvp/id/928, and one from Microchip: http://jimfranklin.info/microchipdatasheets/00699b.pdf.

Let me know if you still want more about anti-alias filters.  My upcoming columns on oversampling explain how using this technique helps eliminate an anti-alias filter for some measurements.

Nancy Golden
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Platinum
Software Solution?
Nancy Golden   7/30/2012 10:58:47 AM
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Great information, Jon - I love your series and how it addresses so many relevant issues in test engineering. I was wondering since this is a mathematical function - is it possible to write a software algorithm to eliminate the unwanted data points and if so - would a hardware solution (anti-aliasing filter) or a software solution (algorithm) be more advantageous - or is that simply a matter of available resources?

Jon Titus
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Blogger
Re: Software Solution?
Jon Titus   7/30/2012 5:42:21 PM
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A software algorithm would have the same problem as people.  It could not distinguish the points from the "wanted" signal from those points acquired by an almost unlimited number of higher-frequency signals.  An anti-alias filter will help.  I find it better to eliminate any source of unwanted signals--noise--as close to the source as possible.  More about filters and how to choose them in my next column.

Nancy Golden
User Rank
Platinum
Re: Software Solution?
Nancy Golden   7/30/2012 6:00:34 PM
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Thanks, Jon. I agree that it is always better for the data to be "real" and noise eliminated at the source is always best which also eliminates the need for data to be massaged by software - I was just wondering if it was an option in this case. Thanks for the information!



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