A singular value decomposition approach to detect chaos in nonlinear circuits and dynamic systems

In this paper the analogy between Lyapunov exponents and the singular values of the covariance matrix is introduced and two new conjectures are stated. On this basis a new numerical procedure to classify the steady-state behavior of nonlinear dynamic systems from noisy time series data is presented. In order to show the suitability of the proposed approach, several applications to time series data gathered from measurements on experimental circuits are reported.<
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