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Let's say that I have 9 sensors arranged in a 3 by 3 grid. I have multiple objects which emit the same signal and move past the grid of sensors, which are picking up the signals. I have a CSV file which contains readings from the 9 sensors collected every 0.01s for up to a minute and I don't know how many objects are in there. How can I find out how many there were?

I think each of the 9 sensors will basically collect very similar readings to each other, but at different time-points (since an object moves past each sensor at a different time). Any ideas on a general approach to these sorts of problems would be welcome too!

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It is fourier transformation problem. All you need to do is to do a fourier transformation of your discrete signal and it will tell all the different frequencies it consists of. Numpy.fft class will be helpful.

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You are describing a variation of the “cocktail party problem,” which refers to the problem of perceiving a signal in a noisy landscape.

One common solution is independent component analysis (ICA), a computational method for separating a multivariate signal into additive subcomponents.

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