Integral Shape Averaging applied to delayed windows of the same signal
Résumé
Integral Shape Averaging (ISA) is a technique for averaging a series of positive signals using their normalized integrals. In case of equal shape signals, ISA gives an estimation of this shape with an increased SNR due to integration. A new application of ISA is presented here: from only one recording of a positive signal embedded in noise, applying ISA to a series of delayed windows containing the signal can give a good estimation of this signal. Simulation results are given on a double and then a triple Gaussian embedded in white zero mean noise, with different SNRs.
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