This time series contains some time frame which each of them are 8K (frequencies)*151 (time samples) in 0.5 sec [overall 1.2288 millions samples per half a second)
- I need to find anomalous based on different rows (frequencies) Report the rows (frequencies) which are anomalous? (an unsupervised learning method)
Do you have an idea to which statistical parameter is more useful for it? or is it possible to evaluate without time sampling?
Do have an idea about suitable fast method (with lowest time delay: therefore some algorithm like kmeans does not work)
I should produce online automated ML