We compare improvements in signal-to-noise in continuous-wave electron paramagnetic resonance (CW EPR) spectra resulting from adaptive signal averaging and a simple moving average. An adaptive filter module that uses a recursive least-squares (RLS) algorithm was incorporated into a CW EPR data acquisition program. After optimization, the RLS filter produces a significant improvement in the signal-to-noise ratio over conventional digital signal (spectral) averaging alone. However, conventional averaging of spectra combined with a central moving average of the data points provided equal or greater signal-to-noise improvement in the CW EPR spectra.
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