DETECTING DETERMINISTIC SIGNALS IN EXCEPTIONALLY NOISY ENVIRONMENTS USING CROSS-RECURRENCE QUANTIFICATION

The demonstrated ability of recurrence quantification analysis to dete ct very subtle patterns in time series was exploited to devise a filte r able to recognize and extract signals buried in large amounts of noi se. The proposed technique, cross-recurrence quantification, demonstra tes the ability to extract signals up to a very low signal-to-noise-ra tio and to allow an immediate appreciation of their degree of periodic ity. The lack of any stationarity dependence of the proposed method op ens the way to many possible applications, including encryption. (C) 1 998 Elsevier Science B.V.