Segmented peak finder, findpeaksSG.mn, has the same syntax as findpeaksG.m, except the 3rd to 6th input
arguments can be vectors with one entry for each segment.
Locates and measures the positive peaks in a noisy x-y time series data.
Detects peaks by looking for downward zero-crossings in the first
derivative whose upward slopes exceed SlopeThreshold. Returns list (P)
containing peak number and position, height, width, and area of each
peak. Arguments "slopeThreshold", "ampThreshold" and "smoothwidth"
control peak sensitivity of each segment. Higher values will neglect
smaller features. "Smoothwidth" is a vector of the widths of the smooths
applied before peak detection; larger values ignore narrow peaks. If
smoothwidth=0, no smoothing is performed. "Peakgroup" is a vector of the
number points around the top part of the peak that are taken for
measurement. If Peakgroup=0 the local maximum is taken as the peak height
and position. The argument "smoothtype" determines the smooth algorithm:
If smoothtype=1, rectangular (sliding-average or boxcar) If
smoothtype=2, triangular (2 passes of sliding-average) If smoothtype=3,
pseudo-Gaussian (3 passes of sliding-average)
See http://terpconnect.umd.edu/~toh/spectrum/Smoothing.html and
(c) T.C. O'Haver, 2016. Version 1, November, 2016
Tom O'Haver (2021). Segmented peak finder findpeaksSG.m (https://www.mathworks.com/matlabcentral/fileexchange/60301-segmented-peak-finder-findpeakssg-m), MATLAB Central File Exchange. Retrieved .
未定义与 'double' 类型的输入参数相对应的函数 'gaussian'。
出错 TestPrecisionFindpeaskSG (line 25)
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