A statistic controlled filter algorithm to reduce random white noise from experimental data is developed. This technique is equivalent to implementing an ideal low‐pass filter where a statistical test is used to determine the cutoff frequency. Moreover, this filter requires no apriori knowledge of the signal and provides an estimate of the noise level. The routine is simple, fast, and easy to implement on a microcomputer.

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