Abstract
This paper presents a method of using the Fourier transform of experimental signals to stochastically develop mean and standard error values of the desired numerical quantities. The application discussed here is an EPR experiment where the fraction of aligned atoms or molecules is related to the second integral of the experimental signal, A computationally efficient Monte Carlo procedure is discussed that selects different estimates of the noise behavior in the signal frequency domain and develops statistical predictions of the second integral value. The algorithm can be used alone or with other filtering operations. Computationally the number of Fourier transforms performed is independent of the number of stochastic trials. This fact allows the algorithm to be applicable to the microcomputer environment.
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