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

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Syed Abdul Salam
Syed Abdul Salam 2019-8-28
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.
  1 个评论
Syed Abdul Salam
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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采纳的回答

Star Strider
Star Strider 2019-8-28
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
Experiment to get the result you want.
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Syed Abdul Salam
Syed Abdul Salam 2019-8-28
Thanks I have done it with the help of your code, just repeating it many times.
function [pks1,locs1] = descending_peaks(pks,locs)
for i = 1:length(pks)-1
dpks = diff([pks(1); pks]); % Non-Descending Will Be Positive
Lv = dpks <= 0; % Logical Vector Mask
pks = pks(Lv); % New Peaks
locs = locs(Lv); % New Locs
end
pks1 = pks;
locs1 = locs;
end
Star Strider
Star Strider 2019-8-28
As always, my pleasure!
I was considering that option as well, although I was considering a one-pass solution. If I develop one, I will post back here.

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