MATLAB >> clipping of data

by Mary Jo » Sun, 31 Dec 2006 15:05:26 GMT

Hi, I am new to matlab and working on a project for school that is
due the 16th. Unfortunately some of the data clipped and the info I
need is at the peak. Is there a way to get an educated guess where
that peak may be? Mary Jo

MATLAB >> clipping of data

by John D'Errico » Sun, 31 Dec 2006 19:46:29 GMT

I'd suggest that you interpolate the
clipped points, replacing them with a
new value imputed from the non-clipped
data. It will work best if the clipping
is internal to the data, so that you
have some valid information on each
end of a clipped region.

If the clipping is at the end of your
data, intelligent extrapolation is a
far more difficult problem. For example,

x = 0:.1:3;
y1 = sin(x);

% clip
y1 = min(y1,0.9);

You can form a decent estimate of where
the maximum truly resides from the above
data. I'd probably fit it with a cubic
spline or use my own inpaint_nans to do
the interpolation. Inpaint_nans is on
the file exchange. In case you are
interested, look here:

<> ;

The spline is simplest here though.
Then use fminbnd to find the max. Your
code might be like this:

% find the un-clipped points
k = (y1 < 0.9);

% fit the spline
spl = spline(x(k),y1(k));

% interpolate
ypred = ppval(spl,x);

% and plot
plot(x(k),y1(k),'ro', ...
x(~k),y1(~k),'gx', ...

Having interpolated the clipped
information, fminbnd can find the
maximum value. Use it to minimize
a function like

fun = @(x) -ppval(spl,x);

ans =

Since the true peak happens at
pi/2, this is reasonably close.

Had the all happened at an end of
your data, all is different, and
much more difficult to do well.
For example,

x = 0:.1:3;
y2 = exp(x);
clipval = 12;
y2 = min(y2,clipval);

k = (y2<clipval);


Extrapolation is more difficult to
do well. Splines are not good at it.
I'd be best off here to fit a well
chosen model to my data, then use it.


MATLAB >> clipping of data

by Rune Allnor » Sun, 31 Dec 2006 20:46:06 GMT

Mary Jo skrev:

Generally speaking: No.

Getting the dynamic range of the setup right is essential
in data acquisition, and lots of effort goes into getting
that right. Once the sensors saturates, amplitude information
is irreversably lost.


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