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Quasi-periodic signals can be contaminated with random distortions (“artifacts”) not manifested periodically and homogenously,without affecting all signal cycles.These distortions cannot be characterized statistically or modelled with a known probability function. In this paper, a stochastic analysis method to detect the presence of such distortions is proposed. The aim of the method is identifying the affected cycles, which exhibit a different morphology compared to the unaffected cycles.The identification of the affected cycles (or non-homogeneous cycles) allows to estimate parameters and extract the useful information needed for a correct characterization of the signal.The method compares nearly periodic signal cycles through the mean square error and the estimated variance of the inherent noise affecting the signal. Expressions are derived to estimate this error and compared with experimental results.

Stochastic Method for Non-Homogeneous Cycles Identification in Quasi-Periodic Signals