Dr Saxe


,new sensors are being introduced continuously which will drive even more use-cases



On 10 axis ( Indoor location)

 However, this baseline represents only a small fraction of the available sensors and the algorithms that can take advantage of them. 

Incorporation of additional inputs and the resulting necessary increase in computational capabilities will further stretch power budgets. 

+

this

 Computational complexity of a Kalman filter increases proportionally with n3, where n is the number of model parameters.  So, even a reduction from 10 to 9 parameters will reduce CPU usage by approximately 30%.

But now they will go from 10 to maybe 12.

and a snip from one of the current job offerings...

• Partner with office of CTO to define best in class platform architecture for new market segments

Nice we want this as it puts us where we can shine.