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?
The company says it anticipates high-definition video for home security and other uses will be the next mature technology integrated into the IoT domain, hence the introduction of its MatrixCam devkit.
Siemens and Georgia Institute of Technology are partnering to address limitations in the current additive manufacturing design-to-production chain in an applied research project as part of the federally backed America Makes program.
Most of the new 3D printers and 3D printing technologies in this crop are breaking some boundaries, whether it's build volume-per-dollar ratios, multimaterials printing techniques, or new materials types.
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