Binary classification algorithm where the input variables are arrays
A very simple approach is to build a detector with a sliding window on which you compute standard deviation. For each slide compute the mean and you can test if the next point after the window is far from mean more than a number of standard deviations. This should work because if the window is not very large it will adapt to the local mean and also if the functions are relatively constant on windows and spikes are large, as they look from your graphs