6.3.7-Numerical Differentiation: Noisy Data

These videos were created to accompany a university course, Numerical Methods for Engineers, taught Spring 2013. The text used in the course was "Numerical Methods for Engineers, 6th ed." by Steven Chapra and Raymond Canale.

[lesnyk]

I've had some success with regressing on a moving window through the data, fitting a straight line to _N_ points at a time (where _N_ is an odd number), and calling the slope of the fitted line dy/dx at the midpoint of the line. Another technique is to slide a 3-point window through the data and compute the quadratic that passes exactly through those points; and again, calculate dy/dx analytically at the midpoint of the window.

Your altitude data made me wonder if it would be practical to analytically differentiate a Fourier approximation to the "mountain".

[ericjin]

hey so what is the reason that conducting numerical integration would attenuate the noise signal?