[TriEmbed] Name these algorithms

Pete Soper pete at soper.us
Sun Oct 25 20:19:02 CDT 2015


These are the bread crumbs I was after, thanks. Sensor data capture 
needs to be interrupt driven if possible to optimize power consumption.

-Pete

On 10/25/2015 02:38 PM, Justis Peters via TriEmbed wrote:
> Pete, the examples you give are all univariate timeseries. I think the 
> solution will be really easy, but I want to better understand your 
> goals. Is it enough to use a Z-score against a rolling window? You 
> seem to be optimizing for something operational here, since you're 
> thinking in terms of interrupts. What are you trying to optimize?
>
> Kind regards,
> Justis
>
> On Sat, Oct 24, 2015 at 5:49 PM, Pete Soper via TriEmbed 
> <triembed at triembed.org <mailto:triembed at triembed.org>> wrote:
>
>     Say I have a sensor for which a measured baseline signal can be
>     used as a steady state but some predefined deviation greater than
>     a given amount can can be defined "interesting" by virtue of an
>     interrupt. With the interrupt can come a sequence of samples
>     (either polled or by reusing the same or different deviation for
>     an interrupt) before the sensor reading changes are declared
>     ended, returning to the old or a new normal baseline level, and
>     the process is set up to be repeated. Meanwhile, between
>     interrupts and sample capturing tasks, a set of samples is
>     compared with previously defined "signatures" to confirm that a
>     set of samples is "complete" and a <something> has or has not been
>     detected. I realize that in many cases there has to be a "moving
>     window" to do with matching up samples and signatures: I'm just
>
>     I'm looking for the math taxonomy to do with this for making
>     filters and pattern matchers, but also practical examples that
>     express specific calculations for use cases.
>
>     Example: A photodetector w a programmable comparator that triggers
>     an mcu interrupt when a light level is above or below threshold,
>     and arrangements for detecting these "signatures":
>      . The moon obscured momentarily by a cloud
>      . A passing car's headlights
>      . Dawn
>      . A cigarette lighter lighting a cigarette
>      . A cigarette lighter used in "music concert style"
>      . Lightning
>
>     I guess the ideal would be a few Wikipedia references to help me
>     begin my education, but some practical examples that allow
>     correlating the math with code that implements the math would be
>     much appreciated.
>
>     Thanks,
>     Pete
>
>
>
>
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