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!
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.
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?
A slew of announcements about new materials and design concepts for transportation have come out of several trade shows focusing on plastics, aircraft interiors, heavy trucks, and automotive engineering. A few more announcements have come independent of any trade shows, maybe just because it's spring.
Samsung's Galaxy line of smartphones used to fare quite well in the repairability department, but last year's flagship S5 model took a tumble, scoring a meh-inducing 5/10. Will the newly redesigned S6 lead us back into star-studded territory, or will we sink further into the depths of a repairability black hole?
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