Python中两个标准化时间序列信号之间的功率相关性？

Question

I have two normalized ([1,0]) signals (images attached). Each signal has many peaks and dips. However, both signal have a maximum at approximately same time (in the attached pics, at 2.5 seconds both signals have maximum value of 1.0). I would to like to run correlation between two signals to have the maximum be at 2.5 s. When I run numpy.correlate, I get a peak at a different time step than where the maximum values are. How can I get a maximum correlation peak at time 2.5 s? Any ideas/suggestions would help greatly. Thanks!

Answer 1

To receive a peak at the right location you have to divide by the number of the summed elements. This can be easily overlooked using the numpy/scipy functions which sums but do not divide by the length.

from scipy.signal import correlate

corr = correlate(x1, x2, 'same')
norm_arr = np.concatenate((np.arange(x1.size / 2)[::-1], np.arange(x1.size / 2)))
corrected_corr = corr / (samples.size - norm_arr)/(np.std(x1)*np.std(x2))