Unsupervised learning algorithms to detect anomaly in waves.

I have a sample of graphs (more than 10000...). that look like in the image below:

I am searching for an unsupervised learning algorithms that can help me to detect anomalous observations.

Here what I suggest for beginning: for every observation I have a collection of points $(x,y)$. With this collection, I find Fourier series with regression (I compute coefficients with the base $\{1,\sin(x),\cos(x),\sin(2x),\cos(2x)\dots\}$). Now I have a set of coefficients instead of waves.

Somebody have an idea how to detect anomaly?

• Too broad/ambitious – leonbloy Nov 26 '14 at 17:37
• can you explain the figures? are they all normal obsevations or? In other words what do you call as anomalous observation? – Seyhmus Güngören Nov 29 '14 at 17:52
• The figures are waves of analogue data (i.e volts of some machine). Anomalus observation are observations that very unsimilar (with specific algorithms that i look for) to the train data. – dmitriy Nov 30 '14 at 7:32