Nonlinear Detection of Weak Pseudoperiodic Signals hidden under the Noise Floor
Abstract
The extraction of weak pseudoperiodic (deterministic) signals buried in a additive Gaussian noisy background is investigated by ap-plying the nonlinear signal detection algorithm, based on phase-space embedding technique, principal component analysis and power spectral analysis. By analyzing Rossler chaotic signals, it is demonstrated that the detection algorithm based on the singular value de-composition of the time-delayed covariance matrix of the reconstructed high-dimensional phase space matrix is able to detect weak pseudoperiodic signals completely hidden beneath the additive Gaussian noise floor at SNR up to –24 dB.. Ill. 4, bibl. 13 (in English; abstracts in English, Russian and Lithuanian).
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