# Looking for clues on a possible method or approach for clustering particle data in the form of pulse shapes [closed]

I'm a biologist by origin, and I'm asking this question to the math community to learn from the vast knowledge that I don't posses myself but is out there in the math field.

Edit: posted on Cross validated as suggested: here

This is a very general question, I know, but I'm also mostly seeking general, inspirational answers and clues to steer me in a new direction. (I'm pretty sure the moderators will have comments about this post, let's hope they are constructive, and perhaps suggestions on what tags to add).

Perhaps this is a bit of a wide net that I'm throwing, but I am not sure in what other way to start a thought process towards possible tracking down existing knowledge on the topic described below. Looking around on google and scientific literature has left me a bit lost as I stumble into too many information that is not what I'm actually looking for.

The question is the following: I am wondering if there are effective ways to compare particle data in the form of signal pulse scans, specifically to separate them into groups of particle types.

• For each particle, the full pulse of 6 channels is recorded.

• Pulses have a wide range in length (nr of datapoints) as particles can be between 0.2 and 2000 um, and pulses are recorded at a speed that comes down to ~10 points + 1 point for every 0.5 um length

• Pulses have a wide range in amplitude. Of the 6 signals, all can vary over several orders of magnitude in maximum value, and high values in 1 signal don't necessarily mean high values in others.

To give some visual information, pulseshapes can look like this:

or pretty much anything in between.

Currently I have done extensive work on clustering algorithms working on derived summary parameters of the pulses such as: Maximum (height) Total (area under the curve) length inertia centre of gravity etc.

This gives quite decent results, but looking at the pulses grouped within one cluster, very often there is still variation in pulses present in the clusters, such as the image below, and hence I wonder if there are ways to do cluster analysis on the actual full pulse shapes.

## closed as off-topic by user44191, YCor, Jan-Christoph Schlage-Puchta, Sean Lawton, Yemon ChoiMar 16 at 16:33

• This question does not appear to be about research level mathematics within the scope defined in the help center.
If this question can be reworded to fit the rules in the help center, please edit the question.

• I believe this question is much better suited for a statistics site like the Stackexchange site CrossValidated. The audience here in large part does not do much in the way of statistics. If you do post in another stackexchange site, add a link to this question (even if it gets closed), and make sure you follow the policies of the other site. (For example, I think Cross validated allows images, but if their Howto says no images, then don't include them.) Gerhard "Hope You Find A Pulse" Paseman, 2019.03.15. – Gerhard Paseman Mar 15 at 17:17
• Thank you for the feedback Gerhard. I reposted it on CrossValidated, seems a better community for the question indeed. Perhaps better to close/delete this one? – Mark Mar 15 at 18:08
• stats.stackexchange.com/questions/397747/… – Mark Mar 15 at 18:09
• I would let the community close it. However, make two edits: edit this post near the top to say something like "posted on Cross validated as suggested", and edit the CV post to link to this post (again as suggested). If the community thinks this should be deleted, it will vote to do so. In general, cross posting is discouraged, but there are exceptions, and courtesy dictates listing the relevant fora. Gerhard "Will Not Vote For Either" Paseman, 2019.03.15. – Gerhard Paseman Mar 15 at 18:21