Reconstructing the jacobian from data with observational noise

Methods for the determination of local dynamical linearization information from experimental time series data are subject to computational artifacts. We investigate the artifacts due to observational noise in the data, and gi ve formulas for the expected values of the reconstructed Jacobian in some s imple cases. The formulas we derive in the case of realistic noise amplitud es are quite different from those for the noiseless case. In turn, spurious Lyapunov exponents in the noisy case are correspondingly different from th e noiseless case.