K. Vibe, J. M. Vesin, On chaos detection methods, International Journal of Bifurcation and Chaos, 1996, 6(3), 529-543.[2]J. Theiler, S. Eubank, A. Longtin, et al., Testing for nonlinearity in time series, the method of surrogate data.[J]. Physica D.1992,58:77-[3]C. Poon, C. K. Merrill, Decrease of cardiac chaos in congestive heart failure, Nature, 1997,389(10), 492-495.[4]M. Barahona, C. Poon, Detection of nonlinear dynamics in short, noisy time series, Nature, 1996,381(5), 215-217.[5]U. Parlitz, L. Kocarev, Using surrogate data analysis for unmasking chaotic communication systems, International Journal of Bifurcation and Chaos, 1997, 7(2), 407-413.[6]D. Prichard, J. Theiler, Generating surrogate data for time series with several simultaneously measured variables, Phys. Rev. Lett., 1994, 73(7), 951-954.[7]J. Theiler, D. Prichard, Constrained-realization Monte-Carlo method for hypothesis testing.[J]. Physica D.1996,94:221-[8]T. Schreiber, A. Schmitz, Improved surrogate data for nonlinearity tests, Phys. Rev. Lett., 1996,77(4), 635-638.[9]J.A. Scheinkman, B. Lebaron, Nonlinear dynamics and stock returns, Journal of Business, 1989,62(3), 311-337.[10]J.L. Breeden, N. H. Packard, Nonlinear analysis of data sampled nonuniformly in time.[J]. Physica D.1992,58:273-[11]M. Small, K. Judd, Detecting nonlinearity in experimental data, International Journal of Bifurcation and Chaos, 1998, 8(6), 1231-1244.
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