Reconstructed dynamics and chaotic signal modeling
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[1] David E. Rumelhart,et al. Predicting the Future: a Connectionist Approach , 1990, Int. J. Neural Syst..
[2] A. Wolf,et al. Determining Lyapunov exponents from a time series , 1985 .
[3] Jose C. Principe,et al. Prediction of Chaotic Time Series with Neural Networks , 1992 .
[4] Paul J. Werbos,et al. Backpropagation Through Time: What It Does and How to Do It , 1990, Proc. IEEE.
[5] D. Ruelle,et al. Ergodic theory of chaos and strange attractors , 1985 .
[6] L. Glass,et al. Oscillation and chaos in physiological control systems. , 1977, Science.
[7] Sawada,et al. Measurement of the Lyapunov spectrum from a chaotic time series. , 1985, Physical review letters.
[8] Hecht-Nielsen. Theory of the backpropagation neural network , 1989 .
[9] L. Chua,et al. Chaos: A tutorial for engineers , 1987, Proceedings of the IEEE.
[10] James P. Crutchfield,et al. Geometry from a Time Series , 1980 .
[11] Martin Casdagli,et al. Nonlinear prediction of chaotic time series , 1989 .
[12] James P. Crutchfield,et al. Equations of Motion from a Data Series , 1987, Complex Syst..
[13] F. Takens. Detecting strange attractors in turbulence , 1981 .
[14] J. Shynk. Adaptive IIR filtering , 1989, IEEE ASSP Magazine.
[15] A. Lapedes,et al. Nonlinear signal processing using neural networks: Prediction and system modelling , 1987 .
[16] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[17] P. Grassberger,et al. Characterization of Strange Attractors , 1983 .