Re: Maxima locating in noisy data

[Judd Storrs]

On Tue, Jun 29, 2010 at 5:30 AM, dirac <address@hidden> wrote:
> I am unsure if this is the purpose of the forum, but I am having problems
> finding a way to locate peaks in some noisy data.

I've found peakdet by Eli Billauer to be useful for finding peaks in
noisy data. It's a different approach than linear filtering. It took
me a while to relocate the project I used it on. I think it can be
found on file exchange, but I think I got it third hand. You adjust
delta to the noise level and the code identifies a series of minima
and maxima that are separated by at least delta. It's a
straight-forward approach that works surprisingly well at times (I
used it with in vivo NMR spectroscopy).

%PEAKDET Detect peaks in a vector
%        [MAXTAB, MINTAB] = PEAKDET(V, DELTA) finds the local
%        maxima and minima ("peaks") in the vector V.
%        MAXTAB and MINTAB consists of two columns. Column 1
%        contains indices in V, and column 2 the found values.
%
%        With [MAXTAB, MINTAB] = PEAKDET(V, DELTA, X) the indices
%        in MAXTAB and MINTAB are replaced with the corresponding
%        X-values.
%
%        A point is considered a maximum peak if it has the maximal
%        value, and was preceded (to the left) by a value lower by
%        DELTA.

% Eli Billauer, 3.4.05 (Explicitly not copyrighted).
% This function is released to the public domain; Any use is allowed.

peakdet.m
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