Any algorithm to separate very high values from a data set?

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Hello everybody,
i have a column of dimensions 10317x1, which contains the reflected voltage values.
We can say out of 10,317 reflected voltages more than 95% of values are diffused reflections which has reflected voltage very low, or around average. Only small percentage (less than 5%) of values are too large because those are specular reflections.
The main goal is to split this 2 type of data. I am looking for some algorithm or any mathematical separation function, which can give me a threshold. A threshold which separates the very high values from rest of the values.
I have attached a normalised histogram of the data. Which shows how my data looks like.
I have highlighted with circle which shows that very few values are of high amplitude.
What i can do is pick out the highest 500 values and separate them, but that would be a manual approach. what i am looking for is a mathematical or algorithm based approach.

Accepted Answer

Akira Agata
Akira Agata on 10 Jan 2019
If you have percentage of outlier (say, 5%), I think you can assume 95th percentiles of a data set as a threshold, like:
% Assuming x is your 10317x1 data array
th = prctile(x,95);
% Index of outlier
idx = x > th;
% Separate the data
xOutlier = x(idx);
xNormal = x(~idx);

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