In this paper, the Minimum Entropy Deconvolution (MED) method, developed for seismic signals, is used to address the problem of period estimation in periodic and quasi-periodic sequences. First, a very intuitive explanation of the MED method is given, using a geometric approach. Then, periodic sequences, which can be viewed as the result of a convolutional process similar to that of seismic signals, are postulated as candidates to be processed by the method. Tests performed on a set of signals - including natural and artificial, periodic and quasiperiodic - produce filter outputs showing the desired comb-type shape. These output markers are successfully used in individual period determination. The MED algorithm operating conditions that lead to useful results are described. In order to introduce the application of the MED method to the problem of pitch determination, voiced speech sequences are included among the examples shown. A complete test set of the Spanish vowels is used to evaluate the performance of the method as a pitch estimator. Results obtained and their qualitative validation reveal its robustness, even for individual period measurement.
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