How can I differentiate without decreasing the length of a vector?
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I have some vectors and want to differentiate them up to second order. I don't want to use "diff" because it reduces the length of vector in higher orders! Is there any other function or method that I differentiate and keep the length of vector constant?
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Jan
2014-7-18
gradient is smarter for calculating derivatives:
x = rand(1, 100);
d2 = gradient(gradient(x));
The Savtizky Golay smoothing filter can be applied to calculate a smoothed derivative by fitting polynmials to local parts of the signal. Look in the FileExchange for many different submissions:
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John D'Errico
2020-3-10
Jan is correct, of course. I might only add one idea, to fit the data using a smoothing spline, then differentiate the spline, and evaluate the derivative spline at the original data points.
spl = csaps(x,y);
spld = fnder(spl);
yprimepred = fnval(spld,x);
As I've done it here, this uses tools from the curve fitting toolbox, though there are alternative ways to implement it too.
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Daniel kiracofe
2014-7-18
My standard approach is to use 2nd order centered difference for the main part of the vector, and use first order forward and backward difference at the boundaries:
function d = cdiff(x, dt)
if (nargin<2)
dt =1 ;
end
d(1) = (x(2) - x(1)) / dt;
d(length(x)) = ( x(end) - x(end-1) ) / dt;
ndx = 2:(length(x)-1);
d(ndx) = (x( ndx+1) - x(ndx-1)) / (2 * dt);
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rnayek
2020-3-10
That is what the 
function in MATLAB does too!
function in MATLAB does too!类别
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