📄 peakfinder info.txt
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FINDPEAKS, version 1.3 September, 2006.
Tom O'Haver, toh@umd.edu
This is a faster version of the original findpeaks function 1.0. It can find and measure 1000 peaks in a 1,000,000 point signal in 13 seconds.
findpeaks
function P=findpeaks(x,y,SlopeThreshold,AmpThreshold,smoothwidth,peakgroup)
Function to locate and measure the positive peaks in a noisy
data sets. Detects peaks by looking for downward zero-crossings
in the smoothed third derivative that exceed SlopeThreshold
and peak amplitudes that exceed AmpThreshold. Determines,
position, height, and approximate width of each peak by least-squares
curve-fitting the log of top part of the peak with a parabola.
Returns a list (in matrix P) containing the peak number and
position, height, and width of each peak.
The 4 parameters are:
SlopeThreshold (SlopeT) - Slope of the smoothed third-derivative that is
taken to indicate a peak. Larger values will neglect small features.
AmpThreshold (AmpT) - Any peaks with height less than this value are ignored.
SmoothWidth - Width of smooth functions applied to data before slope is
measured. Larger values will neglect small features. The best value is
about equal to the half-width of the peaks.
PeakWidth - The number of points around the "top part" of the (unsmoothed)
peak that are taken to estimate the peak heights, positions, and widths.
The best value is about equal to the half-width of the peaks.
DemoFindPeak
A simple demo of the findpeaks function on noisy synthetic data.
Numbers the peaks and prints out the P matrix.
DemoFindPeakG
Demos findpeaksG function on noisy synthetic data. Each peak is
graphed individually and the peak positions, height, and width
estimates are shown. Press any key to move to the next peak.
findpeaksG
function P=findpeaksG(x,y,SlopeThreshold,AmpThreshold,smoothwidth,peakgroup)
Graphic version of the findpeaks function. Shows the fit around each peak
individually. (Used by DemoFindPeakG).
FindPeakSliders
Interactive findpeaks function for pre-defined data in x,y.
Load a typical data set into the vectors x,y, then run this
m-file and adjust the 4 sliders to determine what values of the
parameters give the most reliable peak detection. Peak number and
position, height, and width of each peak is returned in the matrix P.
DemoFindPeakSliders and DemoFindPeakSliders2
Self-contained demos of FindPeakSliders applied to
noisy synthetic data.
FindPeakSlider1, FindPeakSlider2, FindPeakSlider3, FindPeakSlider4,
findpeakslidersRedraw, deriv, secderiv, fastsmooth, boxcar, gaussian.
Functions called by FindPeakSliders and DemoFindPeakSliders
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