How to remove outliers without using filter?

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Hello,
I have a measure results and there are some random outliers with a big negative or positive values (jitter of uC), there are just random, single values, outliers have a similar value.
So, I want to eliminate this values (just take the same value from left or linear interpolation value ((k-1)+(k+1))/2).
My question is, how to detect this values without using medfilt or filloutliers?
In this case outlier is by motor 3, at 48. sec (negative peak).
Array is in attachement. Thank you!
Yellow peak at 4,8 sek
If I use:
FX = gradient(v3);
I get:
0,209265176669710
0,236204049673113
0,549647683628642
-0,0127194313868060
-0,452682745464152
-0,605877560385565
-1,42706647302949
-35,9107931304111
0,321110515084925 -< this is a position of outlier
36,0098773311071
1,55432187084153
0,329500733819600
-1,10153727341736
-0,535656388090509
0,222372662282162
-0,349206720356847

Accepted Answer

KALYAN ACHARJYA
KALYAN ACHARJYA on 14 Dec 2020
Edited: KALYAN ACHARJYA on 14 Dec 2020
Use diff function, more details
result=diff(data);
You will get a large variation in such cases (Use threshold to get the indecies), hope I understand your question.
  2 Comments
Nik Rocky
Nik Rocky on 14 Dec 2020
Thank you very much! It works!
Here is solution:
res1 = find(diff(v1)>20); %find index of outlier
v1(res1)=rdivide((v1(res1-1))+(v1(res1+1)),2); %enter a mean value from left and right

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