How to find the peaks in the signal with descending order only?

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Syed Abdul Salam 2019-8-28

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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/477962-how-to-find-the-peaks-in-the-signal-with-descending-order-only

评论： Star Strider 2019-8-28

The following code find the peaks in my signal perfectly.

[pks,locs] = findpeaks(Power,depth,'MinPeakDistance',100,'MinPeakProminence',4);

But I am more interested in the descending order peaks and the code should exclude the values not following the desceding order pattern.

For instance at locs = [1,2,3,4,5,6,7], pks are [100,80,60,70,50,80].

Required: [pks1,locs1] = function_descending(pks,locs);

I only need pks and corresponding locs which are only in descending order like the result should be locs1=[1,2,3,5] and pks1=[100,80,60,50]. It should exclude the values which contradicts the descending phenomena. The values of 70 at position 4 and 80 at position 6 are excluding because they are higher then all preceeding numbers.

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Syed Abdul Salam 2019-8-28

Example 2:

pks = [100,80,60,70,50,80,90,100,51];

locs = [1,2,3,4,5,6,7,8,9];

result should be

pks1 = [100,80,60,50];

locs1 = [1,2,3,5]

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Answer 1

Star Strider 2019-8-28

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/477962-how-to-find-the-peaks-in-the-signal-with-descending-order-only#answer_389485

在 MATLAB Online 中打开

This works, with the example you provided:

pks = [100,80,60,70,50,80]';
locs = [1,2,3,4,5,6]';
dpks = diff([pks(1); pks]);                     % Non-Descending Will Be Positive
Lv = dpks <= 0;                                 % Logical Vector Mask
pks1 = pks(Lv);                                 % New Peaks
locs1 = locs(Lv);                               % New Locs
figure
plot(locs, pks, '^')
hold on
plot(locs1, pks1, 's')
hold off

It does not do any rigorous checking, and just looks ad adjacent peaks.

You can easily wrap it in a function:

function [pks1,locs1] = descending_peaks(pks,locs)
dpks = diff([pks(1); pks]);                     % Non-Descending Will Be Positive
Lv = dpks <= 0;                                 % Logical Vector Mask
pks1 = pks(Lv);                                 % New Peaks
locs1 = locs(Lv);                               % New Locs
end